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2. SIMILARITIES AND DIFFERENCES IN TEACHING CORPORATE SOCIAL RESPONSIBILITY: EVIDENCE FROM MEXICO AND CANADA

Author

GONZALEZ, Santiago, EROGUL, Murat Sakir, and BARRAGAN, Salvador

Subjects
Corporate Social Responsibility, Stakeholder Theory, Case study, Education and Business, Mexico, Canada, Theory and practice of education, LB5-3640, Science
Abstract

The need to incorporate and develop Corporate Social Responsibility (CSR) within university programs is necessary for future leaders, managers and entrepreneurs. Within the framework of CSR and stakeholder theory the paper contributes a comparative case study that utilizes curriculum and in-depth interview analysis to illustrate not only the similarities and differences in the CSR programs, but how social responsibility is taught in a Mexican and Canadian University context. The main findings are: the CSR program in Mexico is perceived as a strategic management tool that adds value to the organization and does not pay any special attention to the globalization phenomena. Whereas in Canada, social responsibility is founded on ethics, attention to the different stakeholders in a globalized environment is emphasized and the strategic importance of CSR is widely accepted. The paper provides academics and researcher insight into exploring how universities can further facilitate students as stakeholders in considering social responsibility as important and necessary to ensure CSR sustainability in practice.

Published
2016
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4. Contributors

Author

Alippi, Cesare, primary, Brown, David G., additional, Campolo, Maurizio, additional, Choe, Yoonsuck, additional, Duffy, Nigel, additional, Érdi, Péter, additional, Fink, Dan, additional, Francon, Olivier, additional, Galdi, Paola, additional, Gonzalez, Santiago, additional, Gori, Marco, additional, Grossberg, Stephen, additional, Hodjat, Babak, additional, Ieracitano, Cosimo, additional, Kant, Mohak, additional, Kasabov, Nikola Kirilov, additional, Kim, Youngsik, additional, Kozma, Robert, additional, Levine, Daniel S., additional, Li, Qinbo, additional, Liang, Jason, additional, Maggini, Marco, additional, Mammone, Nadia, additional, Meyerson, Elliot, additional, Miikkulainen, Risto, additional, Morabito, Francesco Carlo, additional, Navruzyan, Arshak, additional, Ormandy, Roman, additional, Ozawa, Seiichi, additional, Park, Dookun, additional, Perin, Jose Krause, additional, Raju, Bala, additional, Rawal, Aditya, additional, Samuelson, Frank W., additional, Serra, Angela, additional, Shahrzad, Hormoz, additional, Tagliaferri, Roberto, additional, Tiezzi, Matteo, additional, Werbos, Paul J., additional, and Widrow, Bernard, additional

Published
2024
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5. Expected Impact of the Pass/Fail Scoring System for USMLE Step 1 on the Plastic Surgery Residency Selection Process: A National Survey of Plastics Program Directors.

Author

Powell, Michael, Rhodes, Laila, Gonzalez, Santiago, and Mehta, Sagar

Subjects
national survey, plastic surgery residency, residency program director, step 2, usmle step 1 pass/fail
Abstract

BACKGROUND:  Traditionally, the United States Medical Licensing Examination (USMLE) Step 1 3-digit score has been used as a metric to stratify plastic surgery residency candidates. The transition to a pass/fail exam may impact the manner in which integrated plastic surgery residency program directors (PS-RPD) evaluate candidates. It may also limit opportunities for applicants to differentiate themselves from their counterparts. METHODS: A 14-question survey was distributed via email to 76 PS-RPDs collected from the American Medical Association (AMA) residency program site, FRIEDA. It was sent three times from March 3 - March 14, 2020. McNemar tests were performed on the current metrics of evaluation in comparison to metrics expected to be used in the absence of a 3-digit Step 1 score, assuming a P < 0.05 level for statistical significance.  Results: Of the 76 integrated plastics programs surveyed, 24 PS-RPDs responded (31.6% response rate); 91.3% of PS-RPDs strongly disagree or disagree that Step 1 should be pass/fail; 78.3% of PS-RPDs strongly disagree or disagree that diversity will increase. The top five evaluation metrics PS-RPDs expect to utilize following the transition to pass/fail are: letters of recommendation (87.0%; CI 72% - 100%; p=0.500), Step 2 score (78.3%; CI 60% - 96%; p=0.001), research (56.5%; CI 35% - 78%; p=0.125), elective rotation (56.5%; CI 35% - 78%; p=1.000), and personal knowledge of the applicant (52.2%; CI 30% - 74%; p=0.500).  Conclusions: In the absence of a Step 1 score, PS-RPDs may require more holistic metric(s) to evaluate the best fit for their program. This study found that PS-RPDs expect their candidate evaluation process to remain highly similar with the only statistically significant change being an increased emphasis on the candidates Step 2 score.

Published
2022

8. Spontaneously ruptured hepatocellular carcinoma on non-cirrhotic liver: A prospective case series

Author

Romero-Gutiérrez, Marta, Pascual, Sonia, Márquez, Laura, Gómez-Rubio, Mariano, Miquel, Mireia, Alarcón, Cristina, Ferrer, Teresa, Aracil, Carles, Horta, Diana, Latorre, Raquel, González Santiago, Jesús, Bernal, Vanesa, Fernández, Cristina, Piqueras, Belén, Gutiérrez, María Luisa, Martín, Ana, Morillas, Julia, Morales, Dalia, Blanco, Sonia, Rendón, Paloma, Chico, Inmaculada, Testillano, Milagros, Delgado, Carolina, Matilla, Ana, and Gómez Rodríguez, Rafael

Published
2024
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11. Preventing alpelisib-related hyperglycaemia in HR+/HER2−/PIK3CA-mutated advanced breast cancer using metformin (METALLICA): a multicentre, open-label, single-arm, phase 2 trial

Author

Llombart-Cussac, Antonio, Pérez-Garcia, José Manuel, Ruiz Borrego, Manuel, Tolosa, Pablo, Blanch, Salvador, Fernández-Ortega, Adela, Urruticoechea, Ander, Blancas, Isabel, Saura, Cristina, Rojas, Beatriz, Bermejo, Begoña, Ponce Lorenzo, José, Gion, María, Cortez-Castedo, Patricia, Llabres, Elisenda, Galve, Elena, Cueva, Juan Fernando, López, Ana, Alonso-Romero, José Luis, González-Santiago, Santiago, Martínez de Dueñas, Eduardo, Ciruelos, Eva, Martrat, Griselda, Gener, Petra, Alcalá-López, Daniel, Sampayo-Cordero, Miguel, Gómez-Peralta, Fernando, and Cortés, Javier

Published
2024
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15. Uso de paneles de genes en pacientes con alto riesgo de cáncer digestivo hereditario: documento de posicionamiento de la AEG, SEOM, AEGH y consorcio IMPaCT-GENÓMICA

Author

Carballal, Sabela, Balaguer, Francesc, Bujanda, Luis, Capellá, Gabriel, González Santiago, Santiago, Jover, Rodrigo, Moreira, Leticia, Pineda, Marta, Ruiz-Ponte, Clara, Sánchez Heras, Ana Beatriz, Serrano Blanch, Raquel, Soto, José Luis, Vidal Tocino, Rosario, and Cubiella, Joaquín

Published
2024
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16. CONECT4: Desarrollo de componentes basados en Realidad Mixta, Realidad Virtual Y Conocimiento Experto para generaci\'on de entornos de aprendizaje Hombre-M\'aquina

Author

González, Santiago, García, Alvaro, and Núñez, Ana

Subjects
Computer Science - Human-Computer Interaction
Abstract

This work presents the results of project CONECT4, which addresses the research and development of new non-intrusive communication methods for the generation of a human-machine learning ecosystem oriented to predictive maintenance in the automotive industry. Through the use of innovative technologies such as Augmented Reality, Virtual Reality, Digital Twin and expert knowledge, CONECT4 implements methodologies that allow improving the efficiency of training techniques and knowledge management in industrial companies. The research has been supported by the development of content and systems with a low level of technological maturity that address solutions for the industrial sector applied in training and assistance to the operator. The results have been analyzed in companies in the automotive sector, however, they are exportable to any other type of industrial sector. -- -- En esta publicaci\'on se presentan los resultados del proyecto CONECT4, que aborda la investigaci\'on y desarrollo de nuevos m\'etodos de comunicaci\'on no intrusivos para la generaci\'on de un ecosistema de aprendizaje hombre-m\'aquina orientado al mantenimiento predictivo en la industria de automoci\'on. A trav\'es del uso de tecnolog\'ias innovadoras como la Realidad Aumentada, la Realidad Virtual, el Gemelo Digital y conocimiento experto, CONECT4 implementa metodolog\'ias que permiten mejorar la eficiencia de las t\'ecnicas de formaci\'on y gesti\'on de conocimiento en las empresas industriales. La investigaci\'on se ha apoyado en el desarrollo de contenidos y sistemas con un nivel de madurez tecnol\'ogico bajo que abordan soluciones para el sector industrial aplicadas en la formaci\'on y asistencia al operario. Los resultados han sido analizados en empresas del sector de automoci\'on, no obstante, son exportables a cualquier otro tipo de sector industrial., Comment: 15 pages, 16 figures, in Spanish

Published
2021

19. Whole-genome Mutational Analysis for Tumor-informed Detection of Circulating Tumor DNA in Patients with Urothelial Carcinoma

Author

Nordentoft, Iver, Lindskrog, Sia Viborg, Birkenkamp-Demtröder, Karin, Gonzalez, Santiago, Kuzman, Maja, Levatic, Jurica, Glavas, Dunja, Ptashkin, Ryan, Smadbeck, James, Afterman, Danielle, Lauterman, Tomer, Cohen, Yarin, Donenhirsh, Zohar, Tavassoly, Iman, Alon, Ury, Frydendahl, Amanda, Rasmussen, Mads Heilskov, Andersen, Claus Lindbjerg, Lamy, Philippe, Knudsen, Michael, Polak, Paz, Zviran, Asaf, Oklander, Boris, Agerbæk, Mads, Jensen, Jørgen Bjerggaard, and Dyrskjøt, Lars

Published
2024
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20. Characterizing Hepatitis Delta in Spain and the gaps in its management

Author

Rodríguez-Tajes, Sergio, Palom, Adriana, Giráldez-Gallego, Álvaro, Moreno, Antonio, Urquijo, Juan José, Rodríguez, Manuel, Alvarez-Argüelles, Marta, Diago, Moisés, García-Eliz, María, Fuentes, Javier, Martínez-Sapiña, Ana María, Castillo, Pilar, Casado, Marta, Pérez-Campos, Elena, Muñoz, Raquel, Hernández-Conde, Marta, Morillas, Rosa María, Granados, Rafael, Miquel, Mireia, Morillas, María Julia, García-Retortillo, Monserrat, Carrión, Jose Antonio, Moreno, José María, Montón, Cristina, González-Santiago, Jesús Manuel, Lorente, Sara, Cabezas, Joaquín, Mateos, Beatriz, Vázquez-Rodríguez, Sergio, Díaz-Fontenla, Fernando, Pinazo, José María, Delgado, Mercè, Pérez-Palacios, Domingo, Horta, Diana, Fernández-Marcos, Cristina, López, Carmen, Calleja, José Luis, Fernández, Inmaculada, García-Samaniego, Javier, Forns, Xavier, Buti, María, and Lens, Sabela

Published
2024
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22. High frequency of endoluminal thrombus in patients with ischaemic stroke following AARS-CoV-2 infection

Author

Gómez-Porro, P., Cabal-Paz, B., Valenzuela-Chamorro, S., Desanvicente-Celis, Z., Sabin-Muñoz, J., Ochoa-López, C., Flórez, C., Enríquez-Calzada, S., Martín-García, R., Esain-González, Í., García-Fleitas, B., Silva-Hernández, L., Ruiz-Molina, Á., Gamo-González, E., Durán-Lozano, A., Velasco-Calvo, R., Alba-Alcántara, L., González-Santiago, R., Callejas-Díaz, A., Brea-Álvarez, B., Salazar-Uribe, J.-C., Escamilla-Crespo, C., and Carneado-Ruiz, J.

Published
2024
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23. Alta frecuencia de trombo endoluminal en pacientes con ictus isquémico tras la infección por coronavirus 2019

Author

Gómez-Porro, P., Cabal-Paz, B., Valenzuela-Chamorro, S., Desanvicente, Z., Sabin-Muñoz, J., Ochoa-López, C., Flórez, C., Enríquez-Calzada, S., Martín-García, R., Esain-González, Í., García-Fleitas, B., Silva-Hernández, L., Ruiz-Molina, Á., Gamo-González, E., Durán-Lozano, A., Velasco-Calvo, R., Alba-Alcántara, L., González-Santiago, R., Callejas-Díaz, A., Brea-Álvarez, B., Salazar-Uribe, J.C., Escamilla-Crespo, C., and Carneado-Ruiz, J.

Published
2024
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24. Evolving GAN Formulations for Higher Quality Image Synthesis

Author

Gonzalez, Santiago, Kant, Mohak, and Miikkulainen, Risto

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Generative Adversarial Networks (GANs) have extended deep learning to complex generation and translation tasks across different data modalities. However, GANs are notoriously difficult to train: Mode collapse and other instabilities in the training process often degrade the quality of the generated results, such as images. This paper presents a new technique called TaylorGAN for improving GANs by discovering customized loss functions for each of its two networks. The loss functions are parameterized as Taylor expansions and optimized through multiobjective evolution. On an image-to-image translation benchmark task, this approach qualitatively improves generated image quality and quantitatively improves two independent GAN performance metrics. It therefore forms a promising approach for applying GANs to more challenging tasks in the future.

Published
2021

25. Effective Regularization Through Loss-Function Metalearning

Author

Gonzalez, Santiago and Miikkulainen, Risto

Subjects
Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Statistics - Machine Learning
Abstract

Evolutionary optimization, such as the TaylorGLO method, can be used to discover novel, customized loss functions for deep neural networks, resulting in improved performance, faster training, and improved data utilization. A likely explanation is that such functions discourage overfitting, leading to effective regularization. This paper demonstrates theoretically that this is indeed the case for TaylorGLO: Decomposition of learning rules makes it possible to characterize the training dynamics and show that the loss functions evolved by TaylorGLO balance the pull to zero error, and a push away from it to avoid overfitting. They may also automatically take advantage of label smoothing. This analysis leads to an invariant that can be utilized to make the metalearning process more efficient in practice; the mechanism also results in networks that are robust against adversarial attacks. Loss-function evolution can thus be seen as a well-founded new aspect of metalearning in neural networks.

Published
2020

26. Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription

Author

Francon, Olivier, Gonzalez, Santiago, Hodjat, Babak, Meyerson, Elliot, Miikkulainen, Risto, Qiu, Xin, and Shahrzad, Hormoz

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Machine Learning
Abstract

There is now significant historical data available on decision making in organizations, consisting of the decision problem, what decisions were made, and how desirable the outcomes were. Using this data, it is possible to learn a surrogate model, and with that model, evolve a decision strategy that optimizes the outcomes. This paper introduces a general such approach, called Evolutionary Surrogate-Assisted Prescription, or ESP. The surrogate is, for example, a random forest or a neural network trained with gradient descent, and the strategy is a neural network that is evolved to maximize the predictions of the surrogate model. ESP is further extended in this paper to sequential decision-making tasks, which makes it possible to evaluate the framework in reinforcement learning (RL) benchmarks. Because the majority of evaluations are done on the surrogate, ESP is more sample efficient, has lower variance, and lower regret than standard RL approaches. Surprisingly, its solutions are also better because both the surrogate and the strategy network regularize the decision-making behavior. ESP thus forms a promising foundation to decision optimization in real-world problems.

Published
2020

27. Regularized Evolutionary Population-Based Training

Author

Liang, Jason, Gonzalez, Santiago, Shahrzad, Hormoz, and Miikkulainen, Risto

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Machine Learning
Abstract

Metalearning of deep neural network (DNN) architectures and hyperparameters has become an increasingly important area of research. At the same time, network regularization has been recognized as a crucial dimension to effective training of DNNs. However, the role of metalearning in establishing effective regularization has not yet been fully explored. There is recent evidence that loss-function optimization could play this role, however it is computationally impractical as an outer loop to full training. This paper presents an algorithm called Evolutionary Population-Based Training (EPBT) that interleaves the training of a DNN's weights with the metalearning of loss functions. They are parameterized using multivariate Taylor expansions that EPBT can directly optimize. Such simultaneous adaptation of weights and loss functions can be deceptive, and therefore EPBT uses a quality-diversity heuristic called Novelty Pulsation as well as knowledge distillation to prevent overfitting during training. On the CIFAR-10 and SVHN image classification benchmarks, EPBT results in faster, more accurate learning. The discovered hyperparameters adapt to the training process and serve to regularize the learning task by discouraging overfitting to the labels. EPBT thus demonstrates a practical instantiation of regularization metalearning based on simultaneous training.

Published
2020

28. Optimizing Loss Functions Through Multivariate Taylor Polynomial Parameterization

Author

Gonzalez, Santiago and Miikkulainen, Risto

Subjects
Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Statistics - Machine Learning
Abstract

Metalearning of deep neural network (DNN) architectures and hyperparameters has become an increasingly important area of research. Loss functions are a type of metaknowledge that is crucial to effective training of DNNs, however, their potential role in metalearning has not yet been fully explored. Whereas early work focused on genetic programming (GP) on tree representations, this paper proposes continuous CMA-ES optimization of multivariate Taylor polynomial parameterizations. This approach, TaylorGLO, makes it possible to represent and search useful loss functions more effectively. In MNIST, CIFAR-10, and SVHN benchmark tasks, TaylorGLO finds new loss functions that outperform functions previously discovered through GP, as well as the standard cross-entropy loss, in fewer generations. These functions serve to regularize the learning task by discouraging overfitting to the labels, which is particularly useful in tasks where limited training data is available. The results thus demonstrate that loss function optimization is a productive new avenue for metalearning.

Published
2020

29. Severe Craniofacial Morbidity from a Bean Bag Projectile.

Author

Loomba, Vishalli, Obi-Osuagwu, Osita, Al-Nowaylati, Abdl-Rawf, Rahgozar, Paymon, and Gonzalez, Santiago

Abstract

Bean bag munitions, less-lethal weapons primarily used by law enforcement, can cause severe morbidity. Although bean bag munitions are less likely to cause severe injury when compared with regular gunshot rounds, it is crucial to understand that bean bag munitions may be life-threatening. In this case, we describe our experience with a patient who suffered a zygomaticomaxillary complex fracture, facial nerve injury, and retained munition round in his maxillary sinus from a bean bag projectile shot during an altercation with the police. The patient was urgently transferred to the operating room for extraction of the bean bag munition, and although fracture repair was successful, the patient sustained significant damage to facial nerves, leading to lagophthalmos. To our knowledge, this is the first case report describing a penetrating injury from a bean bag munition that was retained within a facial structure. We will discuss the surgical intervention used for this patient and the review of the current literature on these less-lethal munitions.

Published
2021

30. Self-development Tools Utilized by Plastic Surgeons: A Survey of ASPS Members.

Author

Gonzalez, Santiago, Blumenauer, Brian, Yuen, James, and Golinko, Michael

Abstract

UNLABELLED: The plastic surgery literature is devoid of research on the topic of professional development tools that may be used to enhance performance as a plastic surgeon. After an extensive review of the medical literature, we selected the most frequently referenced professional development tools utilized by plastic surgeons, which included the following: goal setting, positive visualization, scheduled practice, critically analyzing mistakes, professional development conferences, involvement in sports, motivational videos, podcasts & audiobooks, daily morning routines, self-development books, and advice from mentors. METHODS: A 10-question survey was sent to 2542 members of the American Society of Plastic Surgeons (ASPS). The algorithm used to select ASPS members to survey was based on member demographics that would best reflect the views of the entire active society membership. Responses were compared based on demographic factors such as type of practice, gender, and age. RESULTS: A total of 286/2542 (11.25%) ASPS members participated in the survey. Analyzing mistakes (96.3%), goal setting (88.51%), and advice from mentors (85.2%) were most commonly attributed to self-development. Respondents in an academic practice favored conferences and advice from mentors. Participants in a solo practice favored self-help books and morning routines. No statistical differences were observed based on training background. CONCLUSIONS: ASPS members attribute their professional development to setting measurable goals, carefully analyzing surgical mistakes, and guidance from mentors. This information opens the door for continued analysis of professional development within plastic surgery as well as supplement training practices at the resident and post-graduate level.

Published
2021

31. Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes

Author

Dentro, Stefan C, Leshchiner, Ignaty, Haase, Kerstin, Tarabichi, Maxime, Wintersinger, Jeff, Deshwar, Amit G, Yu, Kaixian, Rubanova, Yulia, Macintyre, Geoff, Demeulemeester, Jonas, Vázquez-García, Ignacio, Kleinheinz, Kortine, Livitz, Dimitri G, Malikic, Salem, Donmez, Nilgun, Sengupta, Subhajit, Anur, Pavana, Jolly, Clemency, Cmero, Marek, Rosebrock, Daniel, Schumacher, Steven E, Fan, Yu, Fittall, Matthew, Drews, Ruben M, Yao, Xiaotong, Watkins, Thomas BK, Lee, Juhee, Schlesner, Matthias, Zhu, Hongtu, Adams, David J, McGranahan, Nicholas, Swanton, Charles, Getz, Gad, Boutros, Paul C, Imielinski, Marcin, Beroukhim, Rameen, Sahinalp, S Cenk, Ji, Yuan, Peifer, Martin, Martincorena, Inigo, Markowetz, Florian, Mustonen, Ville, Yuan, Ke, Gerstung, Moritz, Spellman, Paul T, Wang, Wenyi, Morris, Quaid D, Wedge, David C, Van Loo, Peter, Consortium, on behalf of the PCAWG Evolution and Heterogeneity Working Group and the PCAWG, Gonzalez, Santiago, Bowtell, David D, Campbell, Peter J, Cao, Shaolong, Christie, Elizabeth L, Cun, Yupeng, Dawson, Kevin J, Eils, Roland, Garsed, Dale W, Ha, Gavin, Jerman, Lara, Lee-Six, Henry, Mitchell, Thomas J, Oesper, Layla, Peto, Myron, and Raphael, Benjamin J

Subjects
Cancer, Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, DNA Copy Number Variations, DNA, Neoplasm, Databases, Genetic, Drug Resistance, Neoplasm, Genetic Heterogeneity, Humans, Neoplasms, Polymorphism, Single Nucleotide, Whole Genome Sequencing, PCAWG Evolution and Heterogeneity Working Group and the PCAWG Consortium, branching evolution, cancer driver genes, cancer evolution, intra-tumor heterogeneity, pan-cancer genomics, subclonal reconstruction, tumor phylogeny, whole-genome sequencing, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin, and drivers of ITH across cancer types are poorly understood. To address this, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types and identify cancer type-specific subclonal patterns of driver gene mutations, fusions, structural variants, and copy number alterations as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution and provide a pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.

Published
2021

33. Association between use of enhanced recovery after surgery protocols and postoperative complications after gastric surgery for cancer (POWER 4): a nationwide, prospective multicentre study

Author

Farré, Mercè Güell, Font, Roser Farré, del Gobbo, Rafael Diaz, Jimenez, Raquel Sánchez, Reche, Isabel Pérez, Calvo, Belen Gil, García, Jordi Llorca, Sánchez, Laura Carrasco, Llimargas, Cristina Prat, García-Sánchez, Ana María, Martínez-Ragüés, Gema, Gómez-Fernández, María, del-Castillo-Criado, Álvaro, Martínez-Díaz, Ruth, Alegría-Rebollo, Sara, Ferrerode-Paz, Javier, García-Pérez, Cristina, Marcos-Contreras, Sergio, Fernández-García, Diana, Torío-Marcos, Maeva, Fernández, Omar Abdellah, Parreño-Manchado, Felipe Carlos, Martín, María Ángeles, Tena-Guerrero, José María, Palma-González, Estefanía, Flores-Flores, Gustavo, Zugasti-Echarte, Orreaga, Pérez-Bergara, Elena, Hernández-García, Susana, Martín-Vizcaíno, Marta, Yoldi-Murillo, Francisco Javier, Valencia-Alzueta, Maider, Chaveli-Díaz, Carlos, Miranda-Murua, Coro, Yárnoz-Irazábal, Concepción, Botella-Martínez, Sonsoles, López-Pardo, Rafael, Torres-Montalvo, Marta, Pinilla-Pico, Isabel, del-Cojo-Peces, Enrique, del Pilar Rodríguez-Chaparro, María, Gómez-Ríos, Manuel Ángel, del-Río-Regueira, Sara, Mosquera-Rodríguez, Eva, Hernández-Beslmeisl, Jessica, Perozo-Medina, María Alejandra, Darias-Delbey, Beneharo, del Carmen Martín-Lorenzo, María, González-Fariña, Vanessa, Rodríguez-Domínguez, Montserrat, Fernández-de-la-Vega-Medina, Jaime, Berrotarán-Ayub, Pilar, Valín-Martínez, José, Concepción-Santana, Laura, Cruz-Zorio, Raúl, Betancort-Gutiérrez Rodríguez, Dolores, Gómez-Viana, Leticia, Figueiredo, Olalla, Rodríguez, Ariadna, González, Manuel, Iglesias, David, Domínguez-Carrera, José Manuel, Olmo, Jorgedo, Del-Río-Fernández, Sabela, Dos-Santos-Carregal, Laura, Rodríguez-Forja, María Jesús, Campaña-Figueira, Olga, Álvarez-Escudero, Julián, Lesquereux-Martínez, Lucía, Parada-González, Purificación, Montenegro-Romero, Ricardo, Bustamante-Montalvo, Manuel, García-Placín, Ana Rosa, Carpintero-Rama, Carmen, Brea-Bahamonde, Sergio, Torres-Alfonso, José Ramón, Barragán-Serrano, Cristina, Posada-González, María, Salcedo-Cabañas, Gabriel, Vor-wald-Wolfgang, Peter, Otero-Martínez, Isabel, Jove-Alborés, Patricia, López-Otero, Marta, Pardellas-Rivera, Hermelinda, Maruri-Chimeno, Ignacio, González-Fernández, Sonia, Sánchez-Santos, Raquel, Luna-Mendoza, Luis, Lloria-Pons, Enrique, Gramuntell-Marco, Francisco, Cánovas-de-Lucas, Raúl, Sancho-Moya, Cristina, Risco, Raquel, Fernández-Esmerats, Anna, Sanahuja-Blasco, Josep Martí, López-Baamonde, Manuel, Ubré, Marta, Martínez-Pallí, Graciela, Momblán, Dulce, Rivas-Gallardo, Nuria, Sánchez-Martín, Rubén, Moral, Pedro, Navarro, Rosalía, Santé, Luis, Almenta, Esther, Muñoz-Hernández, Henar, Rodríguez-Jiménez, Rita Pilar, Ruiz, Nuria, Peláez, María Teresa, Rojo, Juan José, Gordaliza, Carlota, Jezieniecki, Carlos, Jimenez-Viñas, Carlos, Brugiotti, Carlo, Onchalos-Lopez, Ulices, Llácer-Pérez, Manuel, Batalla, Astrid, Azparren, Gonzalo, Bastitta, Micaela, Cueva, Luisa, Felipe, Mar, Giné, Marta, Gómez, Ana M., India, Inmaculada, Piñol, Santiago, Gimeno-Campos, Maria José, Moreno-Gázquez, Aurora, Llorens-Herrerías, Julio, Del-Castillo-Rodrigo, Gema, Herrero-Bogajo, María Luz, De Miguel-Cabrera, María Isabel, España-Pamplona, José Miguel, Gellida-Vilarroig, María, Jordá-Sanz, Laura, Gil-Trujillo, Silvia, Calatayud-Gómez, Laura, Valencia-Echeverri, Juan David, Baladrón-González, Víctor, Gil-Rendo, Aurora, Sanchez-García, Susana, García-Santos, Esther, Benito, Carmen, Lisbona, Cristina, Benito, Pilar, Correa-Chacón, Olga Cecilia, Alcázar-Urrea, Alejandro, Fernández-López, Ana Belén, Betancourt-Bastidas, Ramiro, Navarro-García, Inmaculada, Romera-Barba, Elena, Mira-Jovells, Nuria, Estevez-Perez, Liz Karime, Saludes-Serra, Judit, Olona-Casas, Carles, Vadillo-Bargalló, Jordi, Jorba-Martín, Rosa, Mojarro, Irene, Lorente, Juan Victor, Longo-Guridi, Pablo, Quintero-Moreno, Ana Maria, Soriano-López, David, de la Peña Gómez-Dominguez, Maria, Prieto-Candau, Cecilia, Hernández-Castillo, Marisol, Jarana, Irene, García-Andreu, Francisco, González-González, Jose, Díaz-Lara, María Dolores, Añón-Iranzo, Elena, Aguiló-Lucia, Javier, Fernandez-Martin, Maria Teresa, Guerra, Yessica, Gimeno-Fernández, Pablo, Iglesias-Morales, Carla, Villalba, Ana María Ríos, Nespereira-García, Paula, Castro-Neira, María José, Ochoa-Díez, María, García-Orallo, Silvia, Mozo-Segurado, Maialen, Gutiérrez-Cabezas, Jose Manuel, Gonzalo-González, Ruben, García-Álvarez, Raquel, Ramiro-Ruíz, Álvaro, González-Cofrade, María, Carvajal-Revuelta, Estefanía, Bellido-López, Ana, Redondo-Cristóbal, Guillermo, Amoza-Pais, Sonia, Díaz-Vico, Tamara, Moreno-Gijón, María, Sanz-Navarro, Sandra, Sanz-Álvarez, Lourdes M, Turienzo-Santos, Estrella Olga, Rodicio-Miravalles, Jose Luis, Rizzo-Ramos, Amaya, Cuéllar-Martínez, Ana, Álvarez-Fernández, Rosa Ana, Fernández-Seijo, Carmen, Álvarez-Barrial, Amelia, Gónzalez-Ortea, Carmen, Fernández-Rodriguez, Silvia, García-González, Nerea, Varela-Rodriguez, Lorena, Berzal-Canga, Elena, García-Díaz-Negrete, Ángela, García-Sánchez, Helena, Saenz-Abos, Javier, Ayuso-Iñigo, Beatriz, Vega-Colón, María, Palacios-Córdoba, Ángela Catalina, Quel-Collado, María Teresa, Olvera-García, Mercedes, Martinez-Sánchez, Agustina, Serrano-Alvarez, Carmen, Ganuza-Martínez, Eunate, Maroño-Boedo, María Jesús, Sánchez-Campos, Alberto, Escontrela-Rodríguez, Blanca Anuncia, Martínez-Ruiz, Alberto, Errazti-Olartecoechea, Gaizka, Rodeño-Esteban, Iratxe, Moreno-Allende, Tamara, Gutierrez-Grijalba, Oihane, Katary-niuk-Di-Costanzo, Yanina, Alvarez-Abad, Irene, Sendino-Cañizares, Patricia, Mifsut-Porcel, Patricia, Sarriugarte-Lasarte, Aingeru, Guerra-Lerma, Mikel, Logroño-Ejea, Margarita, Iturricastillo-Pérez, María Del Carmen, Gastaca-Abasolo, María, Muñoz-Sanz, María José, Iriarte-Zaranton, Ibai, Olea-De-La-Fuente, Erika, Mendiguren-Murua, Ana, Reka-Mediavilla, Lorena, Gastón-Moreno, Alberto, Martínez-De-Aragón-Remirez-De-Esparza, Gabriel Jesús, Sierra-Esteban, Valentín, Montero-Mejías, Gema, Pardo-Martínez, Claudia, Valadés-Periañez, Teresa, Marín-Moreno, Ana, Caro-González, Juan Ricardo, Rodríguez-Pérez, María José, Herrero-Herrero, José Carlos, Renedo-Corcóstegui, Pablo, Martín-Oliva, Alejandro, Fernández-Herrero, Ana Isabel, Andrieu-Estefanía, Nerea, Albaladejo-Magdalena, Javier, Álvarez-Rodriguez, María, Sosa-Rodríguez, Valentina, Fresnedo-Pérez, Raquel María, Gil-Lapetra, Cristina, Bolzoni-Marciel, Beatriz, Herrera-López, Maria Isabel, Setién-Moreno, Fernando, Castro-Costoya, Ana Zulema, Olarra-Nuel, José, De-Vega-Irañeta, Marta, Ugarte-Sierra, Bakarne, Vicente-Rodríguez, Irune, Fernández-Pablos, Francisco Javier, Abad-Alonso, Rafael Alberto, Maniega-Alba, Roberto, Ibáñez-Aguirre, Francisco Javier, Postigo-Morales, Susana, Intxaurraga-Fernández, Karmelo, Telletxea-Benguria, Sorkunde, Outón-Guerrero, Ángela, Acosta-Mérida, María Asunción, de la Plaza-Llamas, Roberto, García-Gil, José Manuel, Gemio-del-Rey, Ignacio Antonio, Cabellos-Olivares, Mercedes, Fernández-García, Raquel, Freitas, Lidia Castro, Alcorta, Beatriz Nacarino, Ayuso, María Martín, González, María Moral, Teruel, David García, Serrat-Puyol, Jordi, Molinas-Bruguera, Joan, Fernández, Sara, Peris-Tomás, Nuria, Díez-Ares, Jose Ángel, Periáñez-Gómez, Dolores, Gonzálvez-Guardiola, Paula, Trullenque-Juan, Ramón, Martínez-Mas, Ezequiel, Martínez, Estefanía, Martín, Julia, Higueras, Raquel, Cuenca, Sara, Martín-Vaquerizo, Beatriz, Espinosa-Moreno, Alma M., Sánchez-Merchante, Miriam, Alcañiz-Sobrino, Rebeca, Egea-Hita, Guillermo, García-del-Valle-y-Manzano, Santiago, Moreno-Blanco, Virginia, Bruna-Esteban, Marcos, Mingol-Navarro, Fernando, Vaqué-Urbaneja, Javier, Díaz-Cambronero, Óscar, Luján-Sandemetrio, Beatriz, Copariate-Piqueras, Bisila, Giménez-Salcedo, Sonia, Ripolles-Melchor, Javier, Abad-Motos, Ane, Abad-Gurumeta, Alfredo, Aracil-Escoda, Norma, Saez-Ruiz, Elena, Salva-chua-Fernandez, Rut, Paseiro-Crespo, Gloria, García-Nebreda, María, Toribio, Begoña, Ferrero-Celemin, Esther, García-Sancho-Téllez, Luis, Sánchez-López, José Daniel, Núñez O'Sullivan, Sara, Gar-cía-Virosta, Mariana, Rodriguez-Haro, Carmen, Hernández-O’Reilly, María, Suarez-de-la-Rica, Alejandro, Lopez-Martinez, Mercedes, Croes, Bryant, Mujica, Jaime, Maseda, Emilio, Alday-Muñoz, Enrique, Mata-Mena, Esperanza, García-Sanz, Iñigo, Marín, Cristina, Muñoz, Antonio Pedraza, Dominguez, Jorge Puertas, González-López, Rocío, Navarro-Quirós, Gisela, Pérez-Moreiras, M. Isabel, Conde-Rodriguez, María, Muinelo-Lorenzo, Manuel, Díez-Zapirain, Miren Jasone, Tejón-Pérez, Guillermo, Álvarez-Cebrián, María Asunción, Barrero-Ruiz, Eva, Capa-Fuertes, Eva, Carrillo-Rivas, Mariana, Hernandez-Sanchez, Isabel, Monteagudo-Cimiano, Valvanuz, Pascual-Casado, Ángela, Rábago-Morillón, Jose Luis, Martinez-Ubieto, Javier, Pascual-Bellosta, Ana, Ortega-Lucea, Sonia, Perez-Otal, Berta, Tardos-Ascaso, Lucia, Ligorred-Padilla, Luis Antonio, Tur-Martínez, Jaume, Rodríguez-Santiago, Joaquin, Pérez-Romero, Noelia, Puértolas-Rico, Noelia, Hernández-Giménez, Laura, Concepción-Martín, Vanessa, Molnar, Viktoria, Barbero, Macarena, San-Antonio, Belén, Pueyo, Alberto, Mayo-Ossorio, M de los Angeles, Bengoechea-Trujillo, Ander, Pacheco-Garcia, José Manuel, Diez-Remesal, Yolanda, Gonzalo-Millán, Alba, Berruezo-Camacho, Alberto, Alaez-Cortés, Azucena, Ortolá-Rocher, Begoña, Iglesias-Gallego, Berta, Martín-Montero, Eduardo, Arias-Cuesta, Gerardo, de la Hoz-Polo, Inés, Recuero-Torrijos, Isabel, Pereira-Torres, Lucia, Cañamas-Catalá, Maria, Martin-González, Maria C., Zambrana-García, Paloma, Llorente-Damas, Sergio, Aldecoa, Cesar, Perez-Gonzalez, Alba, Bolaño-Perez, Clara, Velasco-Andres, Delia, Aguado-Saster, Esther, Arranz, Irene, Mendez-Torrubiano, Itziar, Vaquero-Perez, Laura, Sanz-de-Leon, Maria Jesus, Rodicio, Pablo, Martin-Alfonso, Silvia, Martin-Tappi, David, Madrid-Tribano, Mario, Rioja-Garrido, Rocio, Morales-Jaquete, Borja, Vicente-Orgaz, Marta, Orozco-Vinasco, Adriana Carolina, Fraga-Casais, Gema, Miyagi-Yonamine, Any Minerva, Ramos-de-Castro, Raquel, Mejía-Arnaud, Rossel Alina, Saz-Castro, Rubén, Díaz-Peña, Patricia, Camps-Cervantes, Angels, Tormos-Perez, M Pilar, Galan-Menendez, Patricia, Esclapez-Sampere, Elena, Villarino-Villa, Laura, Loaiza-Aldeán, Yuri, Chocron-Dapratt, Ivette, Martinez-Silva, Olga, Matarin-Olmo, Silvia, Berges-Gutiérrez, Héctor, Pérez-Serrano, Macarena, Diaz-Castillo, Juan Javier, Sancho-Muñoz-de-Verger, Álvaro, Villanueva-Mena-Bernal, Jesús Alejandro, Gil-Gómez, Maria Lucia, Fernanz-Anton, Jesús, Marmaña-Mezquita, Sandra, Galofré-Pujol, Gonzalo, Jericó, Carlos, Motos-Micó, José Jacob, Orts-Micó, Francisco José, Serra-Díaz, Carlos, Arlandis-Félix, Francisco, Pérez-Climent, Nieves, Blanes-Pastor, Lorena, Jover-Pinillos, Jose Luis, Salvaterra, David, Linero, Manuel, Galipienzo, Javier, Alonso, Óscar, Ortega, Gloria, Gonzalez, Santiago, Lopez-Rojo, Irene, Ripollés-Melchor, Javier, Abdel-lah Fernández, Omar, Tormos-Pérez, María P., A Mayo-Ossorio, María, Gil-Gómez, Lucia, Parreño-Manchado, Felipe C, De-Miguel-Cabrera, María I, García-Erce, José A., Río-Fernández, Sabela del, Herrero-Bogajo, María L., Zorrilla-Vaca, Andrés, Vaquero-Pérez, Laura, Fernández-Martín, María T., Ferrando-Ortolà, Carlos, Ramírez-Rodríguez, José M., and Aldecoa, César

Published
2023
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34. Ipatasertib (IPA) combined with non-taxane chemotherapy (CT) for patients (pts) with previously treated advanced triple-negative breast cancer (aTNBC): The PATHFINDER phase IIa trial.

Author

Lopez-Miranda, Elena, primary, Pérez García, José Manuel, additional, Gion, Maria, additional, Ribelles, Nuria, additional, Cortez, Patricia, additional, Alonso Romero, Jose Luis, additional, Martínez-García, María, additional, Gonzalez- Santiago, Santiago, additional, Bermejo, Begoña, additional, Morales Murillo, Serafin, additional, Carañana, Vicente, additional, Garrigós, Laia, additional, Fernández, Melissa, additional, Boix, Olga, additional, Alcalá-López, Daniel, additional, Cortes, Javier, additional, and Llombart, Antonio, additional

Published
2024
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35. Neuraxial Analgesia in Pregnant Hispanic Women: An Assessment of Their Beliefs and Expectations.

Author

Gonzalez, Basilia, Gonzalez, Santiago, Rojo, Martha, and Mhyre, Jill

Subjects
Hispanic, childbirth, neuraxial analgesia, pain management, pregnancy, racial disparities
Abstract

BACKGROUND: The presence of racial/ethnic disparities in the use of neuraxial labor analgesia for childbirth has been previously described. The purpose of this study was to assess the childbirth pain management beliefs among a small sample of pregnant Hispanic women and to evaluate the Spanish translation accuracy of the Childbirth Pain Scale (CPBS). METHODS: To collect data, we interviewed 20 pregnant Spanish-speaking women using an interview guide, a demographic datasheet, and the CPBS a 15-item survey. Interviews were transcribed verbatim, translated, and uploaded to ethnograph v6. Descriptive statistics and thematic analysis were used to analyze the data. RESULTS: Most of the participants were from Mexico (n=16) and Central America (n=4), mean age was 28.3, and all (n=20) spoke Spanish as their primary language. In this sample, 80% of nulliparous and 100% of multiparous women saw pain as having a positive role in delivery. Four major themes emerged from the data: Theme 1: Normalcy of childbirth pain (pain is good), Theme 2: Availability and role of pain medication, Theme 3: Naturalistic strategies to endure pain, and Theme 4: Fear of the unknown/childbirth process. In this sample, 18 of 20 women stated they did not want epidural analgesia unless medically indicated. During labor and delivery 100% of nulliparous and 25% of multiparas chose to receive epidural analgesia. No changes were requested by the participants regarding the translation of the CPBS. CONCLUSION: Childbirth pain was seen as a valuable component of the birthing process. The majority of participants believed pain medication should be avoided unless medically necessary. These results suggest that racial/ethnic disparities in the use of epidural analgesia may partially reflect patient beliefs and preferences. It is crucial to be aware of these differences to optimize shared decision-making for women in this vulnerable patient population.

Published
2021

36. Untethered and HIPAA-compliant Interactive Livestreaming of Surgery to Residents and Medical Students.

Author

Yuen, James, Gonzalez, Santiago, Osborn, Tamara, and Abu-Rmaileh, Muhammad

Abstract

Traditional livestreaming of surgery to an audience requires stationary video broadcasting infrastructure, with viewers congregating in front of a screen, while audiovisual technicians provide support in the background. In recent years, livestreaming technologies from cameras to teleconference platforms have advanced dramatically, even to allow for compliance with the Health Insurance Portability and Accountability Act of 1996 with web-based encryption. The objective of this article is to show that livestreaming surgery in medical education is possible using portable devices, with the resident and medical students as audience at home interacting on their computer or smart devices. The surgeon utilizes a head-mounted camera transmitting video feed using a wireless transmitter broadcasting to a laptop computer, which is hosting a Health Insurance Portability and Accountability Act-compliant version of Zoom. The entire setup is portable, and the surgeon is tethered neither to a cord nor to the institutions audiovisual enterprise. This prototype setup allows the surgeon to broadcast live surgery interactively at any time and from any operating room with remote medical students and surgical residents. We posit that our medical education industry would need to condense the devices into a turnkey livestreaming camera system with optimized frames per second reception.

Published
2020

37. Improved Training Speed, Accuracy, and Data Utilization Through Loss Function Optimization

Author

Gonzalez, Santiago and Miikkulainen, Risto

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing, Statistics - Machine Learning
Abstract

As the complexity of neural network models has grown, it has become increasingly important to optimize their design automatically through metalearning. Methods for discovering hyperparameters, topologies, and learning rate schedules have lead to significant increases in performance. This paper shows that loss functions can be optimized with metalearning as well, and result in similar improvements. The method, Genetic Loss-function Optimization (GLO), discovers loss functions de novo, and optimizes them for a target task. Leveraging techniques from genetic programming, GLO builds loss functions hierarchically from a set of operators and leaf nodes. These functions are repeatedly recombined and mutated to find an optimal structure, and then a covariance-matrix adaptation evolutionary strategy (CMA-ES) is used to find optimal coefficients. Networks trained with GLO loss functions are found to outperform the standard cross-entropy loss on standard image classification tasks. Training with these new loss functions requires fewer steps, results in lower test error, and allows for smaller datasets to be used. Loss-function optimization thus provides a new dimension of metalearning, and constitutes an important step towards AutoML.

Published
2019

38. The evolutionary history of 2,658 cancers

Author

Gerstung, Moritz, Jolly, Clemency, Leshchiner, Ignaty, Dentro, Stefan C, Gonzalez, Santiago, Rosebrock, Daniel, Mitchell, Thomas J, Rubanova, Yulia, Anur, Pavana, Yu, Kaixian, Tarabichi, Maxime, Deshwar, Amit, Wintersinger, Jeff, Kleinheinz, Kortine, Vázquez-García, Ignacio, Haase, Kerstin, Jerman, Lara, Sengupta, Subhajit, Macintyre, Geoff, Malikic, Salem, Donmez, Nilgun, Livitz, Dimitri G, Cmero, Marek, Demeulemeester, Jonas, Schumacher, Steven, Fan, Yu, Yao, Xiaotong, Lee, Juhee, Schlesner, Matthias, Boutros, Paul C, Bowtell, David D, Zhu, Hongtu, Getz, Gad, Imielinski, Marcin, Beroukhim, Rameen, Sahinalp, S Cenk, Ji, Yuan, Peifer, Martin, Markowetz, Florian, Mustonen, Ville, Yuan, Ke, Wang, Wenyi, Morris, Quaid D, Spellman, Paul T, Wedge, David C, and Van Loo, Peter

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Bioinformatics and Computational Biology, Genetics, Oncology and Carcinogenesis, Rare Diseases, Brain Cancer, Brain Disorders, Human Genome, Cancer, 2.1 Biological and endogenous factors, Aetiology, DNA Repair, Evolution, Molecular, Gene Dosage, Genes, Tumor Suppressor, Genetic Variation, Genome, Human, Humans, Mutagenesis, Insertional, Neoplasms, PCAWG Evolution & Heterogeneity Working Group, PCAWG Consortium, General Science & Technology
Abstract

Cancer develops through a process of somatic evolution1,2. Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes3. Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)4, we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection.

Published
2020

39. A shortest-path based clustering algorithm for joint human-machine analysis of complex datasets

Author

Pizzagalli, Diego Ulisse, Gonzalez, Santiago Fernandez, and Krause, Rolf

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction
Abstract

Clustering is a technique for the analysis of datasets obtained by empirical studies in several disciplines with a major application for biomedical research. Essentially, clustering algorithms are executed by machines aiming at finding groups of related points in a dataset. However, the result of grouping depends on both metrics for point-to-point similarity and rules for point-to-group association. Indeed, non-appropriate metrics and rules can lead to undesirable clustering artifacts. This is especially relevant for datasets, where groups with heterogeneous structures co-exist. In this work, we propose an algorithm that achieves clustering by exploring the paths between points. This allows both, to evaluate the properties of the path (such as gaps, density variations, etc.), and expressing the preference for certain paths. Moreover, our algorithm supports the integration of existing knowledge about admissible and non-admissible clusters by training a path classifier. We demonstrate the accuracy of the proposed method on challenging datasets including points from synthetic shapes in publicly available benchmarks and microscopy data.

Published
2018
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40. Pinning Control to Regulate Cellular Response in Cancer for the p53-Mdm2 Genetic Regulatory Network

Author

Suarez, Oscar J., Vega, Carlos J., Sanchez, Edgar N., Chen, Guanrong, González-Santiago, Ana E., Rodríguez-Jorge, Otoniel, Alanis, Alma Y., Hernandez-Vargas, Esteban A., Zelinka, Ivan, Series Editor, Adamatzky, Andrew, Series Editor, Chen, Guanrong, Series Editor, Abraham, Ajith, Editorial Board Member, Lucia, Ana, Editorial Board Member, Burguillo, Juan C., Editorial Board Member, Čelikovský, Sergej, Editorial Board Member, Chadli, Mohammed, Editorial Board Member, Corchado, Emilio, Editorial Board Member, Davendra, Donald, Editorial Board Member, Ilachinski, Andrew, Editorial Board Member, Lampinen, Jouni, Editorial Board Member, Middendorf, Martin, Editorial Board Member, Ott, Edward, Editorial Board Member, Pan, Linqiang, Editorial Board Member, Păun, Gheorghe, Editorial Board Member, Richter, Hendrik, Editorial Board Member, Rodriguez-Aguilar, Juan A., Editorial Board Member, Rössler, Otto, Editorial Board Member, Snasel, Vaclav, Editorial Board Member, Vondrák, Ivo, Editorial Board Member, Zenil, Hector, Editorial Board Member, and Balaz, Igor, editor

Published
2022
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41. MQTT Based Event Detection System for Structural Health Monitoring of Buildings

Author

Palacios, Iván, Placencia, José, Muñoz, Milton, Samaniego, Víctor, González, Santiago, Jiménez, Juan, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Botto-Tobar, Miguel, editor, Cruz, Henry, editor, Díaz Cadena, Angela, editor, and Durakovic, Benjamin, editor

Published
2022
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48. Primary Chylopericardium: Unveiling an Atypical Presentation

Author

Font Rivera, D., primary, Torres, J.W., additional, Torrens Olan, J., additional, Quiles-Cruz, C.V., additional, Collazo Santiago, H., additional, Gonzalez Santiago, G.M., additional, Ortiz Velez, I., additional, Fernandez, R., additional, and Boodoosingh, D.R., additional

Published
2024
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50. Unveiling a Mystery: Cryptogenic Organizing Pneumonia Emergence Post-COVID-19

Author

Ortiz Velez, I., primary, Torrens Olan, J., additional, Gonzalez Santiago, G.M., additional, Quiles-Cruz, C.V., additional, Font Rivera, D., additional, Collazo Santiago, H., additional, Torres, J.W., additional, Rosado Jimenez, M., additional, Hernandez-Castillo, R.A., additional, Fernandez, R., additional, and De Jesus Vargas, L.A., additional

Published
2024
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