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1. Learning to Select Goals in Automated Planning with Deep-Q Learning

Author

Núñez-Molina, Carlos, Fernández-Olivares, Juan, and Pérez, Raúl

Subjects
Computer Science - Artificial Intelligence, I.2.8, I.2.6
Abstract

In this work we propose a planning and acting architecture endowed with a module which learns to select subgoals with Deep Q-Learning. This allows us to decrease the load of a planner when faced with scenarios with real-time restrictions. We have trained this architecture on a video game environment used as a standard test-bed for intelligent systems applications, testing it on different levels of the same game to evaluate its generalization abilities. We have measured the performance of our approach as more training data is made available, as well as compared it with both a state-of-the-art, classical planner and the standard Deep Q-Learning algorithm. The results obtained show our model performs better than the alternative methods considered, when both plan quality (plan length) and time requirements are taken into account. On the one hand, it is more sample-efficient than standard Deep Q-Learning, and it is able to generalize better across levels. On the other hand, it reduces problem-solving time when compared with a state-of-the-art automated planner, at the expense of obtaining plans with only 9% more actions., Comment: 25 pages, 4 figures

Published
2024
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7. Towards a Unified Framework for Sequential Decision Making

Author

Núñez-Molina, Carlos, Mesejo, Pablo, and Fernández-Olivares, Juan

Subjects
Computer Science - Artificial Intelligence, I.2.8
Abstract

In recent years, the integration of Automated Planning (AP) and Reinforcement Learning (RL) has seen a surge of interest. To perform this integration, a general framework for Sequential Decision Making (SDM) would prove immensely useful, as it would help us understand how AP and RL fit together. In this preliminary work, we attempt to provide such a framework, suitable for any method ranging from Classical Planning to Deep RL, by drawing on concepts from Probability Theory and Bayesian inference. We formulate an SDM task as a set of training and test Markov Decision Processes (MDPs), to account for generalization. We provide a general algorithm for SDM which we hypothesize every SDM method is based on. According to it, every SDM algorithm can be seen as a procedure that iteratively improves its solution estimate by leveraging the task knowledge available. Finally, we derive a set of formulas and algorithms for calculating interesting properties of SDM tasks and methods, which make possible their empirical evaluation and comparison., Comment: 10 pages, 0 figures

Published
2023

9. Soil Elevation Change in Mangrove Forests and Marshes of the Greater Everglades: A Regional Synthesis of Surface Elevation Table-Marker Horizon (SET-MH) Data

Author

Feher, Laura C., Osland, Michael J., McKee, Karen L., Whelan, Kevin R. T., Coronado-Molina, Carlos, Sklar, Fred H., Krauss, Ken W., Howard, Rebecca J., Cahoon, Donald R., Lynch, James C., Lamb-Wotton, Lukas, Troxler, Tiffany G., Conrad, Jeremy R., Anderson, Gordon H., Vervaeke, William C., Smith III, Thomas J., Cormier, Nicole, From, Andrew S., and Allain, Larry

Published
2024
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10. On Using Admissible Bounds for Learning Forward Search Heuristics

Author

Núñez-Molina, Carlos, Asai, Masataro, Mesejo, Pablo, and Fernández-Olivares, Juan

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning, I.2.8
Abstract

In recent years, there has been growing interest in utilizing modern machine learning techniques to learn heuristic functions for forward search algorithms. Despite this, there has been little theoretical understanding of what they should learn, how to train them, and why we do so. This lack of understanding has resulted in the adoption of diverse training targets (suboptimal vs optimal costs vs admissible heuristics) and loss functions (e.g., square vs absolute errors) in the literature. In this work, we focus on how to effectively utilize the information provided by admissible heuristics in heuristic learning. We argue that learning from poly-time admissible heuristics by minimizing mean square errors (MSE) is not the correct approach, since its result is merely a noisy, inadmissible copy of an efficiently computable heuristic. Instead, we propose to model the learned heuristic as a truncated gaussian, where admissible heuristics are used not as training targets but as lower bounds of this distribution. This results in a different loss function from the MSE commonly employed in the literature, which implicitly models the learned heuristic as a gaussian distribution. We conduct experiments where both MSE and our novel loss function are applied to learning a heuristic from optimal plan costs. Results show that our proposed method converges faster during training and yields better heuristics., Comment: 19 pages, 2 figures

Published
2023

12. A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making

Author

Núñez-Molina, Carlos, Mesejo, Pablo, and Fernández-Olivares, Juan

Subjects
Computer Science - Artificial Intelligence, A.2, I.2.4, I.2.6, I.2.8
Abstract

In the field of Sequential Decision Making (SDM), two paradigms have historically vied for supremacy: Automated Planning (AP) and Reinforcement Learning (RL). In the spirit of reconciliation, this article reviews AP, RL and hybrid methods (e.g., novel learn to plan techniques) for solving Sequential Decision Processes (SDPs), focusing on their knowledge representation: symbolic, subsymbolic, or a combination. Additionally, it also covers methods for learning the SDP structure. Finally, we compare the advantages and drawbacks of the existing methods and conclude that neurosymbolic AI poses a promising approach for SDM, since it combines AP and RL with a hybrid knowledge representation., Comment: 35 pages, 16 figures

Published
2023
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13. Extracting Temporal Association Rules Over Datacubes

Author

Molina, Carlos, Prados-Suárez, Belén, 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, Yang, Xin-She, editor, Sherratt, R. Simon, editor, Dey, Nilanjan, editor, and Joshi, Amit, editor

Published
2024
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14. Clinico-radiological features of intracranial atherosclerosis-related large vessel occlusion prior to endovascular treatment

Author

Rodrigo-Gisbert, Marc, García-Tornel, Alvaro, Requena, Manuel, Vielba-Gómez, Isabel, Bashir, Saima, Rubiera, Marta, De Dios Lascuevas, Marta, Olivé-Gadea, Marta, Piñana, Carlos, Rizzo, Federica, Muchada, Marian, Rodriguez-Villatoro, Noelia, Rodríguez-Luna, David, Juega, Jesus, Pagola, Jorge, Hernández, David, Molina, Carlos A., Terceño, Mikel, Tomasello, Alejandro, and Ribo, Marc

Published
2024
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15. NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems

Author

Núñez-Molina, Carlos, Mesejo, Pablo, and Fernández-Olivares, Juan

Subjects
Computer Science - Artificial Intelligence, I.2.6, I.2.8
Abstract

In the field of Automated Planning there is often the need for a set of planning problems from a particular domain, e.g., to be used as training data for Machine Learning or as benchmarks in planning competitions. In most cases, these problems are created either by hand or by a domain-specific generator, putting a burden on the human designers. In this paper we propose NeSIG, to the best of our knowledge the first domain-independent method for automatically generating planning problems that are valid, diverse and difficult to solve. We formulate problem generation as a Markov Decision Process and train two generative policies with Deep Reinforcement Learning to generate problems with the desired properties. We conduct experiments on three classical domains, comparing our approach against handcrafted, domain-specific instance generators and various ablations. Results show NeSIG is able to automatically generate valid and diverse problems of much greater difficulty (15.5 times more on geometric average) than domain-specific generators, while simultaneously reducing human effort when compared to them. Additionally, it can generalize to larger problems than those seen during training., Comment: 15 pages, 9 figures

Published
2023

18. Platelet Analysis in the Thrombus Plus Serum BNP for Detecting Clot-Related Atrial Fibrillation. Results From the ITACAT Multicentric Registry

Author

Pagola, Jorge, Juega, Jesus, Dorado, Laura, Hernandez-Perez, Maria, Lazaro, Carlos, Garcia-Tornel, Alvaro, Olive, Marta, Requena, Manuel, Rubiera, Marta, Muchada, Marian, Rodriguez-Villatoro, Noelia, Rodriguez-Luna, David, Quesada, Helena, Hernandez, David, Piñana, Carlos, de-la-Torre, Carolina, Ribo, Marc, Camacho, Jessica, Ramon-y-Cajal, Santiago, Tomasello, Alejandro, and Molina, Carlos

Published
2023
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20. What is a Challenging Clot?: A DELPHI Consensus Statement from the CLOTS 7.0 Summit

Author

Ospel, Johanna M., Mirza, Mahmood, Clarençon, Frédéric, Siddiqui, Adnan, Doyle, Karen, Consoli, Arturo, Mokin, Maxim, Ullberg, Teresa, Zaidat, Osama, Bourcier, Romain, Kulcsar, Zsolt, Gounis, Matthew J., Liebeskind, David S., Fiehler, Jens, Narata, Ana Paula, Ribo, Marc, Jovin, Tudor, Sakai, Nobuyuki, Rai, Ansaar, McCarthy, Ray, Dorn, Franziska, Andersson, Tommy, Majoie, Charles B. L. M., Hanel, Ricardo, Jadhav, Ashutosh, Riedel, Christian, Chamorro, Angel, Brinjikji, Waleed, Costalat, Vincent, DeMeyer, Simon F., Nogueira, Raul G., Cognard, Christophe, Montaner, Joan, Leung, Thomas W., Molina, Carlos, van Beusekom, Heleen, Davalos, Antoni, Weisel, John, Chapot, Rene, Möhlenbruch, Markus, and Brouwer, Patrick

Published
2023
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22. Multi-ancestry GWAS reveals excitotoxicity associated with outcome after ischaemic stroke

Author

Ibanez, Laura, Heitsch, Laura, Carrera, Caty, Farias, Fabiana HG, Del Aguila, Jorge L, Dhar, Rajat, Budde, John, Bergmann, Kristy, Bradley, Joseph, Harari, Oscar, Phuah, Chia Ling, Lemmens, Robin, Viana Oliveira Souza, Alessandro A, Moniche, Francisco, Cabezas-Juan, Antonio, Arenillas, Juan Francisco, Krupinksi, Jerzy, Cullell, Natalia, Torres-Aguila, Nuria, Muiño, Elena, Cárcel-Márquez, Jara, Marti-Fabregas, Joan, Delgado-Mederos, Raquel, Marin-Bueno, Rebeca, Hornick, Alejandro, Vives-Bauza, Cristofol, Navarro, Rosa Diaz, Tur, Silvia, Jimenez, Carmen, Obach, Victor, Segura, Tomas, Serrano-Heras, Gemma, Chung, Jong Won, Roquer, Jaume, Soriano-Tarraga, Carol, Giralt-Steinhauer, Eva, Mola-Caminal, Marina, Pera, Joanna, Lapicka-Bodzioch, Katarzyna, Derbisz, Justyna, Davalos, Antoni, Lopez-Cancio, Elena, Muñoz, Lucia, Tatlisumak, Turgut, Molina, Carlos, Ribo, Marc, Bustamante, Alejandro, Sobrino, Tomas, Castillo-Sanchez, Jose, Campos, Francisco, Rodriguez-Castro, Emilio, Arias-Rivas, Susana, Rodríguez-Yáñez, Manuel, Herbosa, Christina, Ford, Andria L, Gutierrez-Romero, Alonso, Uribe-Pacheco, Rodrigo, Arauz, Antonio, Lopes-Cendes, Iscia, Lowenkopf, Theodore, Barboza, Miguel A, Amini, Hajar, Stamova, Boryana, Ander, Bradley P, Sharp, Frank R, Kim, Gyeong Moon, Bang, Oh Young, Jimenez-Conde, Jordi, Slowik, Agnieszka, Stribian, Daniel, Tsai, Ellen A, Burkly, Linda C, Montaner, Joan, Fernandez-Cadenas, Israel, Lee, Jin Moo, and Cruchaga, Carlos

Subjects
Epidemiology, Health Sciences, Human Genome, Stroke, Genetics, Brain Disorders, Biotechnology, Neurosciences, 2.1 Biological and endogenous factors, Aetiology, Neurological, Bayes Theorem, Brain Ischemia, Genome-Wide Association Study, Humans, Ischemic Stroke, United States, ischaemic stroke, neuroprotection, genetics, NIHSS, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

During the first hours after stroke onset, neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between the National Institutes of Health Stroke Scale (NIHSS) within 6 h of stroke onset and NIHSS at 24 h. A total of 5876 individuals from seven countries (Spain, Finland, Poland, USA, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of NIHSS at 24 h of variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture from that of stroke risk. Eight loci (1p21.1, 1q42.2, 2p25.1, 2q31.2, 2q33.3, 5q33.2, 7p21.2 and 13q31.1) were genome-wide significant and explained 1.8% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each locus. Expression quantitative trait loci mapping and summary data-based Mendelian randomization indicate that ADAM23 (log Bayes factor = 5.41) was driving the association for 2q33.3. Gene-based analyses suggested that GRIA1 (log Bayes factor = 5.19), which is predominantly expressed in the brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated GNPAT (log Bayes factor = 7.64) ABCB5 (log Bayes factor = 5.97) for the 1p21.1 and 7p21.1 loci. Human brain single-nuclei RNA-sequencing indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a presynaptic protein and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provide the first genetic evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischaemic stroke.

Published
2022

24. Tenecteplase versus alteplase for thrombolysis in patients selected by use of perfusion imaging within 4·5 h of onset of ischaemic stroke (TASTE): a multicentre, randomised, controlled, phase 3 non-inferiority trial

Author

Phan, Timmy, Selmes, Christine, Lees, Kennedy, Kaste, Markku, MacIsaac, Rachael, Wellings, Tom, Loiselle, Andre, Pepper, Elizabeth, Miteff, Ferdi, Krishnamurthy, Venkatesh, Ang, Timothy, Alanati, Khaled, Gangadharan, Shyam, Zareie, Hossein, Starling, Rita, Dunkerton, Sophie, He, Jiacheng, Datta, Raka, Royan, Angela, Kerr, Erin, Kaauwai, Lara, Belevski, Linda, Ormond, Sally, Johnson, Annalese, Evans, Malcolm, Lachapelle, Nicole, Ombelet, Fouke, Bladin, Chris, Dewey, Helen, Wong, Joseph, Park, Peter, Cody, Ross, Tan, Peter, Callaly, Edward, Senanayake, Channa, Thomas, Grace, Liu, Jennifer, Busch, Tessa, Stuart, Narelle, Chung, Malcohm, Yassi, Nawaf, Valente, Michael, Sharobeam, Angelos, Cooley, Regan, Zhao, Henry, Alemseged, Fana, Williams, Cameron, Ng, Jo Lyn, Balabanski, Anna, dos Santos, Angela, Williamson, John, Pavlin-Premrl, Davor, Beharry, James, Ma, Margaret, Park, Ashley, Yan, Bernard, Hand, Peter, Jackson, David, McDonald, Amy, Fisicchia, Laura, Parsons, Nicola, Olenko, Liudmyla, Johns, Hannah, Guha, Prodipta, Rokaha, Birendra, Dhimal, Niruta, Harvey, Jackson, Cagi, Lavenia, Chia, Nicholas, Goh, Rudy, Palanikumar, Log, El-Masri, Shaddy, Mahadevan, Joshua, Kuranawai, Craig, Waters, Michael, Vallat, Wilson, Cheong, Eddie, Drew, Roy, Cordato, Dennis, McDougall, Alan, Cappelen-Smith, Cecilia, Venkat, Abhay, Edwards, Leon, Blair, Christopher, Thomas, James, Helou, Jacob, Green, Daniel, Nguyen, Tram, Pham, Timmy, Khan, Jasmeen, Miller, Megan, Loubiere, Laurence, Buck, Brian, Butcher, Ken, Fairall, Paige, Butt, Asif, Kalashyan, Hayrapet, Nomani, Ali, Lloret, Mar, Mishra, Sachin, Thirunavukkarasu, Sibi, Sivakumar, Leka, D'Souza, Atlantic, Tsai, Chon-Haw, Tseng, Billy, Tai, Iris, Chiang, I-Husan, Kuan, Angela, Tsai, Vivian, Hsu, Alice, Hsu, Sammi, Alchin, Deborah, Sanjuan, Estela, Fink, John, Wilson, Duncan, Mason, Deborah, Berry-Norohna, Alexander, Winders, Joel, Eagle, Jane, Green, Rosemary, Bremner, Kathleen, Celestino, Sherisse, Lee, Jiunn-Tay, Chou, Chung-Hsing, Tsai, Chia-Kuang, Sung, Yueh-Feng, Tsai, Chia-Lin, Lin, Yu-Kai, Kao, Hung-Wen, Vuong, Jason, Thirugnanachandran, Tharani, Hervet, Marie Veronic, Simmons, Karen, Sabet, Arman, Bailey, Peter, Urbi, Berzenn, Kurakose, Sumole, Martinez-Majander, Nicolas, Räty, Silja, Tiainen, Marjaana, Sibolt, Gerli, Ivanoff, Terhi, Sanz, Ana Calleja, García, Elisa Cortijo, De Lera Alfonso, Mercedes C., Araque, Maria Ester Ramos, Gómez, Alicia Sierra, Peñacoba, Gonzalo Valle, Vicente, Beatriz Gómez, Muñoz, Javier Reyes, Muñoz Rubio, Pedro Luis, Shah, Darshan, Harrison, Emma, Bendall, Carol, Subramanian, Ganesh, Jeng, Jiann-Shing, Tang, Sung-Chun, Tsai, Li-Kai, Yeh, Shin-Joe, Chen, Chih-Hao, Chung, Tai-Chun, Wong, Andrew, Muller, Claire, Skinner, Genevieve, Gunathilagan, Gunaratnam, Natarajan, Indira, Coutts, Shelagh, Menon, Bijoy, Kenney, Carol, Clarke, Brian, Ghatala, Rita, Mudd, Paul, Chen, Chih-Hung, Lemmens, Robin, Demeestere, Jelle, Mahant, Neil, Sun, Mu-Chien, Parsons, Mark W, Yogendrakumar, Vignan, Churilov, Leonid, Garcia-Esperon, Carlos, Campbell, Bruce C V, Russell, Michelle L, Sharma, Gagan, Chen, Chushuang, Lin, Longting, Chew, Beng Lim, Ng, Felix C, Deepak, Akshay, Choi, Philip M C, Kleinig, Timothy J, Cordato, Dennis J, Wu, Teddy Y, Fink, John N, Ma, Henry, Phan, Thanh G, Markus, Hugh S, Molina, Carlos A, Strbian, Daniel, Meretoja, Atte, Arenillas, Juan F, Buck, Brian H, Devlin, Michael J, Brown, Helen, Butcher, Ken S, O'Brien, Billy, Wijeratne, Tissa, Bivard, Andrew, Grimley, Rohan S, Agarwal, Smriti, Munshi, Sunil K, Donnan, Geoffrey A, Davis, Stephen M, Miteff, Ferdinand, Spratt, Neil J, and Levi, Christopher R

Published
2024
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27. Reto Ciudad Naturaleza, La Paz: una experiencia de observación y registro de la biodiversidad urbana/City Nature Challenge, La Paz: An Example of Observing and Recording Urban Biodiversity/Reto Ciudad Naturaleza La Paz: uma experiência de observação e registo da biodiversidade urbana

Author

Flores-Turdera, Cecilia, Wallace, Robert, Caritano-Zavala, Alvaro, Maldonado, Carla, Jurado, Cynthya, Alvarez-Portugal, Daniela, Angulo, Wilma, Ayala, Cuido, Gómez, M. Isabel, Hayes, Mayli, Molina, Carlos, Salinas, Elvira, and Torrico, Ornar

Published
2023
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30. Granulocytes-Rich Thrombi in Cerebral Large Vessel Occlusion Are Associated with Increased Stiffness and Poorer Revascularization Outcomes

Author

Juega, Jesús, Li, Jiahui, Palacio-Garcia, Carlos, Rodriguez, Maite, Tiberi, Riccardo, Piñana, Carlos, Rodriguez-Luna, David, Requena, Manuel, García-Tornel, Álvaro, Rodriguez-Villatoro, Noelia, Rubiera, Marta, Muchada, Marian, Olivé-Gadea, Marta, Rizzo, Federica, Hernandez, David, Dios-Lascuevas, Marta, Hernandez-Perez, Maria, Dorado, Laura, Quesada, Helena, Cardona, Pere, De La Torre, Carolina, Gallur, Laura, Camacho, Jessica, Ramon-y-Cajal, Santiago, Tomasello, Alejandro, Ribó, Marc, Molina, Carlos A., and Pagola, Jorge

Published
2023
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32. Thrombolysis for Wake-Up Stroke Versus Non–Wake-Up Unwitnessed Stroke: EOS Individual Patient Data Meta-Analysis

Author

Kamogawa, Naruhiko, Miwa, Kaori, Toyoda, Kazunori, Jensen, Märit, Inoue, Manabu, Yoshimura, Sohei, Fukuda-Doi, Mayumi, Kitazono, Takanari, Boutitie, Florent, Ma, Henry, Ringleb, Peter, Wu, Ona, Schwamm, Lee H., Warach, Steven, Hacke, Werner, Davis, Stephen M., Donnan, Geoffrey A., Gerloff, Christian, Thomalla, Götz, Koga, Masatoshi, Cheng, Bastian, Bendszus, Martin, Bladin, Christopher, Churilov, Leonid, Campbell, Brunce, Parsons, Mark, Yassi, Nawaf, Ebinger, Martin, Endres, Matthias, Fiebach, Jochen B., Kleinig, Timothy, Latour, Lawrence, Lemmens, Robin, Levi, Christopher, Leys, Didier, Molina, Carlos, Muir, Keith, Nighoghossian, Norbert, Pedraza, Salvador, Schellinger, Peter D., Schwab, Stefan, Simonsen, Claus Z., Song, Shlee S., Thijs, Vincent, Toni, Danilo, Hsu, Chung Y., and Wahlgren, Nils

Published
2024
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33. Radial Versus Femoral Access for Mechanical Thrombectomy in Patients With Stroke: A Noninferiority Randomized Clinical Trial

Author

Hernandez, David, Requena, Manuel, Olivé-Gadea, Marta, de Dios, Marta, Gramegna, Laura Ludovica, Muchada, Marian, García-Tornel, Álvaro, Diana, Francesco, Rizzo, Federica, Rivera, Eila, Rubiera, Marta, Piñana, Carlos, Rodrigo-Gisbert, Marc, Rodríguez-Luna, David, Pagola, Jorge, Carmona, Tomás, Juega, Jesús, Rodríguez-Villatoro, Noelia, Molina, Carlos, Ribo, Marc, and Tomasello, Alejandro

Published
2024
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34. Predictors of Recurrent Stroke After Embolic Stroke of Undetermined Source in the RE‐SPECT ESUS Trial

Author

Del Brutto, Victor J, Diener, Han‐Christoph, Easton, J Donald, Granger, Christopher B, Cronin, Lisa, Kleine, Eva, Grauer, Claudia, Brueckmann, Martina, Toyoda, Kazunori, Schellinger, Peter D, Lyrer, Philippe, Molina, Carlos A, Chutinet, Aurauma, Bladin, Christopher F, Estol, Conrado J, and Sacco, Ralph L

Subjects
Neurosciences, Stroke, Brain Disorders, Clinical Trials and Supportive Activities, Clinical Research, Prevention, Aspirin, Cerebral Infarction, Dabigatran, Embolic Stroke, Humans, Intracranial Embolism, Male, Risk Factors, Tomography, Emission-Computed, Single-Photon, embolic stroke of undetermined source, risk factors, secondary prevention, stroke predictors, Cardiorespiratory Medicine and Haematology
Abstract

Background We sought to determine recurrent stroke predictors among patients with embolic strokes of undetermined source (ESUS). Methods and Results We applied Cox proportional hazards models to identify clinical features associated with recurrent stroke among participants enrolled in RE-SPECT ESUS (Randomized, Double-Blind, Evaluation in Secondary Stroke Prevention Comparing the Efficacy and Safety of the Oral Thrombin Inhibitor Dabigatran Etexilate Versus Acetylsalicylic Acid in Patients With Embolic Stroke of Undetermined Source) trial, an international clinical trial evaluating dabigatran versus aspirin for patients with ESUS. During a median follow-up of 19 months, 384 of 5390 participants had recurrent stroke (annual rate, 4.5%). Multivariable models revealed that stroke or transient ischemic attack before the index event (hazard ratio [HR], 2.27 [95% CI, 1.83-2.82]), creatinine clearance

Published
2022

35. Planning from video game descriptions

Author

Vellido, Ignacio, Núñez-Molina, Carlos, Nikolov, Vladislav, and Fdez-Olivares, Juan

Subjects
Computer Science - Artificial Intelligence
Abstract

This project proposes a methodology for the automatic generation of action models from video game dynamics descriptions, as well as its integration with a planning agent for the execution and monitoring of the plans. Planners use these action models to get the deliberative behaviour for an agent in many different video games and, combined with a reactive module, solve deterministic and no-deterministic levels. Experimental results validate the methodology and prove that the effort put by a knowledge engineer can be greatly reduced in the definition of such complex domains. Furthermore, benchmarks of the domains has been produced that can be of interest to the international planning community to evaluate planners in international planning competitions., Comment: To be submitted to the Knowledge Engineering Review (KER) journal

Published
2021

36. Tenecteplase versus standard of care for minor ischaemic stroke with proven occlusion (TEMPO-2): a randomised, open label, phase 3 superiority trial

Author

Salluzzi, Marina, Blenkin, Nicole, Dueck, Ashley, Doram, Craig, Zhang, Qiao, Kenney, Carol, Ryckborst, Karla, Bohn, Shelly, Collier, Quentin, Taylor, Frances, Lethebe, B. Cord, Jambula, Anitha, Sage, Kayla, Toussaint, Lana, Save, Supryia, Lee, Jaclyn, Laham, N, Sultan, A.A., Deepak, A., Sitaram, A., Demchuk, Andrew M., Lockey, A., Micielli, A., Wadhwa, A., Arabambi, B., Graham, B., Bogiatzi, Chrysi, Doshi, Darshan, Chakraborty, D., Kim, Diana, Vasquez, D, Singh, D, Tse, Dominic, Harrison, E., Smith, E.E., Teleg, E., Klourfeld, E., Klein, G., Sebastian, I.A., Evans, J, Hegedus, J, Kromm, J, Lin, K, Ignacio, K, Ghavami, Kimia, Ismail, M., Moores, M., Panzini, M.A., Boyko, M., Almekhlafi, M.A., Newcommon, Nancy, Maraj, N., Imoukhuede, O., Volny, O., Stys, Peter, Couillard, Phillipe, Ojha, P., Eswaradass, P., Joundi, Raed, Singh, R., Asuncion, R.M., Muir, R.T., Dey, S., Mansoor, S., Wasyliw, S., Nagendra, S., Hu, Sherry, Althubait, S., Chen, S., Bal, S., Van Gaal, Stephen, Peters, Steven, Ray, Sucharita, Chaturvedi, S., Subramaniam, Suresh, Fu, Vivian, Villaluna, K., Maclean, G., King-Azote, P., Ma, C., Plecash, A., Murphy, C., Gorman, J., Wilson, L., Zhou, L., Benevente, O., Teal, P., Yip, S., Mann, S., Dewar, B., Demetroff, M., Shamloul, R., Beardshaw, R., Roberts, S., Blaquiere, D., Stotts, G., Shamy, M., Bereznyakova, O., Fahed, R., Alesefir, W., Lavoie, Suzy, Hache, A., Collard, K, Mackey, A., Gosselin-Lefebvre, S., Verreault, S., Beauchamp, B., Lambourn, L., Khaw, A., Mai, L., Sposato, L., Bres Bullrich, M., Azarpazhooh, R., Fridman, S., Kapoor, A., Southwell, A., Bardi, E., Fatakdawala, I., Kamra, M, Lopes, K., Popel, N., Norouzi, V., Liu, A., Liddy, A.M., Ghoari, B., Hawkes, C., Enriquez, C.A., Gladstone, D.J., Manosalva Alzate, H.A., Khosravani, H., Hopyan, J.J., Sivakumar, K., Son, M., Boulos, M.I., Hamind, M.A., Swartz, R.H., Murphy, R., Reiter, S., Fitzpatrick, T., Bhandari, V., Good, J., Penn, M., Naylor, M., Frost, S., Cayley, A., Akthar, F., Williams, J., Kalman, L., Crellin, L., Wiegner, R., Singh, R.S., Stewart, T., To, W., Singh, S., Pikula, A., Jaigobin, C., Carpani, F., Silver, F., Janssen, H., Schaafsma, J., del Campo, M., Alskaini, M., Rajendram, P., Fairall, P., Granfield, B., Crawford, D., Jabs, J., White, L., Sivakumar, L., Piquette, L., Nguyen, T., Nomani, A., Wagner, A., Alrohimi, A., Butt, A., D'Souza, A., Gajurel, B., Vekhande, C., Kamble, H., Kalashyan, H., Lloret, M., Benguzzi, M., Arsalan, N., Ishaque, N., Ashayeriahmadabad, R., Samiento, R., Hosseini, S., Kazi, S., Das, S., Sugumar, T., Selchen, D., Kostyrko, P., Muccilli, A., Saposnik, A.G., Vandervelde, C., Ratnayake, K., McMillan, S., Katsanos, A., Shoamanesh, A., Sahlas, D.J., Naidoo, V., Todorov, V., Toma, H., Brar, J., Lee, J., Horton, M., Shand, E., Weatherby, S., Jin, A., Durafourt, B., Jalini, S., Gardner, A., Tyson, C., Junk, E., Foster, K., Bolt, K., Sylvain, N., Maley, S., Urroz, L., Peeling, L., Kelly, M., Whelan, R., Cooley, R., Teitelbaum, J., Boutayeb, A., Moore, A., Cole, E., Waxman, L., Ben-Amor, N., Sanchez, R., Khalil, S., Nehme, A., Legault, C., Tampieri, D., Ehrensperger, E., Vieira, L., Cortes, M., Angle, M., Hannouche, M., Badawy, M., Werner, K., Wieszmuellner, S., Langer, A., Gisold, A., Zach, H., Rommer, P., Macher, S., Blechinger, S., Marik, W., Series, W., Baumgartinger, M., Krebs, S., Koski, J., Eirola, S., Ivanoff, T., Erakanto, A., Kupari, L., Sibolt, G., Panula, J., Tomppo, L., Tiainen, M., Ahlstrom, M., Martinez Majander, N., Suomalainen, O., Raty, S., Levi, C., Kerr, E., Allen, J., Kaauwai, L.P., Belevski, L., Russell, M., Ormond, S., Chew, A., Loiselle, A., Royan, A., Hughes, B., Garcia Esperon, C., Pepper, E., Miteff, F., He, J., Lycett, M., Min, M., Murray, N., Pavey, N., Starling de Barros, R., Gangadharan, S., Dunkerton, S., Waller, S., Canento Sanchez, T., Wellings, T., Edmonds, G., Whittaker, K.A., Ewing, M., Lee, P., Singkang, R., McDonald, A., Dos Santos, A., Shin, C., Jackson, D., Tsoleridis, J., Fisicchia, L., Parsons, N., Shenoy, N., Smith, S., Sharobeam, A., Balabanski, A., Park, A., Williams, C., Pavlin-Premri, D., Rodrigues, E., Alemseged, F., Ng, F., Zhao, H., 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Pancorbo, O., Sala, V., Garcia, L., Garcia-Tornel, A., Juega, J., Pagola, J., Santana, K., Requena, M., Muchada, M., Olive, M., Lozano, P.J., Rubiera, M., Deck, M., Rodriguez, N., Gomez, B., Reyes Munoz, F.J., Gomez, A.S., Sanz, A.C., Garcia, E.C., Penacoba, G., Ramos, M.E., de Lera Alfonso, M., Feliu, A, Pardo, L., Ramirez, P., Murillo, A., Lopez Dominguez, D., Rodriguez, J., Terceno Izaga, M., Reina, M., Viturro, S.B., Bojaryn, U., Vera Monge, V.A., Silva Blas, Y., R Siew, R., Agustin, S J, Seet, C., Tianming, T., d'Emden, A., Murray, A., Welch, A., Hatherley, K., Day, N., Smith, W., MacRae, E., Mitchell, E.S., Mahmood, A., Elliot, J., Neilson, S., Biswas, V., Brown, C., Lewis, A., Ashton, A., Werring, D., Perry, R., Muhammad, R., Lee, Y.C., Black, A., Robinson, A., Williams, A., Banaras, A., Cahoy, C., Raingold, G., Marinescu, M., Atang, N., Bason, N., Francia, N., Obarey, S., Feerick, S., Joseph, J., Schulz, U., Irons, R., Benjamin, J., Quinn, L., Jhoots, M., Teal, R., Ford, G., Harston, G., Bains, H., Gbinigie, I., Mathieson, P., Sim, C.H., Hayter, E., Kennedy, K., Binnie, L., Priestley, N., Williams, R., Ghatala, R., Stratton, S., Blight, A., Zhang, L., Davies, A., Duffy, H., Roberts, J., Homer, J., Roberts, K., Dodd, K., Cawley, K., Martin, M., Leason, S., Cotgreave, S., Taylor, T., Nallasivan, A., Haider, S., Chakraborty, T., Webster, T., Gil, A., Martin, B., Joseph, B., Cabrera, C., Jose, D., Man, J., Aquino, J., Sebastian, S., Osterdahl, M., Kwan, M., Matthew, M., Ike, N., Bello, P., Wilding, P., Fuentes, R., Shah, R., Mashate, S., Patel, T., Nwanguma, U., Dave, V., Haber, A., Lee, A., O'Sullivan, A., Drumm, B., Dawson, A.C., Matar, T., Roberts, D., Taylor, E., Rounis, E., El-Masry, A., O'Hare, C., Kalladka, D., Jamil, S., Auger, S., Raha, O., Evans, M., Vonberg, F., Kalam, S., Ali Sheikh, A., Jenkins, I.H., George, J., Kwan, J., Blagojevic, J., Saeed, M., Haji-Coll, M., Tsuda, M., Sayed, M., Winterkron, N., Thanbirajah, N., Vittay, O., Karim, R., Smail, 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A., Hutchinson, C., Kirkland, C., Newham, J., Wilkes, G., Fleming, L., Fleck, N., Franca, A., Chwal, B., Oldoni, C., Mantovani, G., Noll, G., Zanella, L., Soma, M., Secchi, T., Borelli, W., Rimoli, B.P., da Cunha Silva, G.H., Machado Galvao Mondin, L.A., Barbosa Cerantola, R., Imthon, A.K., Esaki, A.S., Camilo, M., Vincenzi, O.C., ds Cruz, R.R., Morillos, M.B., Riccioppa Rodrigues, G.G., Santos Ferreira, K., Pazini, A.M., Pena Pereira, M.A., de Albuquerque, A.L.A., Massote Fontanini, C.E., Matinez Rubio, C.F., dos Santos, D.T., Dias, F.A., Alves, F.F.A., Milani, C., Pegorer Santos, B., Winckler, F., De Souza, J.T., Bonome, L.A.M., Cury Silva, V.A., Teodoro, R.S., Modolo, G.P., Ferreira, N.C., Barbosa dos Santos, D.F., dos Santos Moreira, J.C., Cruz Guedes de Morais, A.B., Vieira, J., Mendes, G., de Queiroz, J.P., Coutts, Shelagh B, Ankolekar, Sandeep, Appireddy, Ramana, Arenillas, Juan F, Assis, Zarina, Bailey, Peter, Barber, Philip A, Bazan, Rodrigo, Buck, Brian H, Butcher, Ken S, Camden, Marie-Christine, Campbell, Bruce C V, Casaubon, Leanne K, Catanese, Luciana, Chatterjee, Kausik, Choi, Philip M C, Clarke, Brian, Dowlatshahi, Dar, Ferrari, Julia, Field, Thalia S, Ganesh, Aravind, Ghia, Darshan, Goyal, Mayank, Greisenegger, Stefan, Halse, Omid, Horn, Mackenzie, Hunter, Gary, Imoukhuede, Oje, Kelly, Peter J, Kennedy, James, Kleinig, Timothy J, Krishnan, Kailash, Lima, Fabricio, Mandzia, Jennifer L, Marko, Martha, Martins, Sheila O, Medvedev, George, Menon, Bijoy K, Mishra, Sachin M, Molina, Carlos, Moussaddy, Aimen, Muir, Keith W, Parsons, Mark W, Penn, Andrew M W, Pille, Arthur, Pontes-Neto, Octávio M, Roffe, Christine, Serena, Joaquin, Simister, Robert, Singh, Nishita, Spratt, Neil, Strbian, Daniel, Tham, Carol H, Wiggam, M Ivan, Williams, David J, Willmot, Mark R, Wu, Teddy, Yu, Amy Y X, Zachariah, George, Zafar, Atif, Zerna, Charlotte, and Hill, Michael D

Published
2024
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38. Neuro-inspired edge feature fusion using Choquet integrals

Author

Marco-Detchart, Cedric, Lucca, Giancarlo, Lopez-Molina, Carlos, De Miguel, Laura, Dimuro, Graçaliz Pereira, and Bustince, Humberto

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

It is known that the human visual system performs a hierarchical information process in which early vision cues (or primitives) are fused in the visual cortex to compose complex shapes and descriptors. While different aspects of the process have been extensively studied, as the lens adaptation or the feature detection, some other,as the feature fusion, have been mostly left aside. In this work we elaborate on the fusion of early vision primitives using generalizations of the Choquet integral, and novel aggregation operators that have been extensively studied in recent years. We propose to use generalizations of the Choquet integral to sensibly fuse elementary edge cues, in an attempt to model the behaviour of neurons in the early visual cortex. Our proposal leads to a full-framed edge detection algorithm, whose performance is put to the test in state-of-the-art boundary detection datasets.

Published
2021
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40. Safety and efficacy of platelet glycoprotein VI inhibition in acute ischaemic stroke (ACTIMIS): a randomised, double-blind, placebo-controlled, phase 1b/2a trial

Author

Albucher, Jean François, Alonso, Angelika, Berrouschot, Jörg, Cordonnier, Charlotte, de Raedt, Sylvie, Desfontaines, Philippe, Doche, Emilie, Hemelsoet, Dimitri, Macian-Montoro, Francisco, Masjuan, Jaime, Obadia, Michael, Peeters, André, Pelz, Johann, Reiner, Peggy, Segura, Tomas, Serena, Joaquin, Sibon, Igor, Tembl, Jose I., Vannier, Stéphane, Zuber, Mathieu, Mazighi, Mikaël, Köhrmann, Martin, Lemmens, Robin, Lyrer, Philippe A, Molina, Carlos A, Richard, Sébastien, Toni, Danilo, Plétan, Yannick, Sari, Anouar, Meilhoc, Adeline, Jandrot-Perrus, Martine, Binay, Sophie, Avenard, Gilles, Comenducci, Andrea, Grouin, Jean-Marie, and Grotta, James C

Published
2024
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44. Safety and efficacy of factor XIa inhibition with milvexian for secondary stroke prevention (AXIOMATIC-SSP): a phase 2, international, randomised, double-blind, placebo-controlled, dose-finding trial

Author

Sharma, Mukul, Molina, Carlos A, Toyoda, Kazunori, Bereczki, Daniel, Bangdiwala, Shrikant I, Kasner, Scott E, Lutsep, Helmi L, Tsivgoulis, Georgios, Ntaios, George, Czlonkowska, Anna, Shuaib, Ashfaq, Amarenco, Pierre, Endres, Matthias, Yoon, Byung-Woo, Tanne, David, Toni, Danilo, Yperzeele, Laetitia, von Weitzel-Mudersbach, Paul, Sampaio Silva, Gisele, Avezum, Alvaro, Dawson, Jesse, Strbian, Daniel, Tatlisumak, Turgut, Eckstein, Jens, Ameriso, Sebastián F, Weber, Joerg R, Sandset, Else Charlotte, Goar Pogosova, Nana, Lavados, Pablo M, Arauz, Antonio, Gailani, David, Diener, Hans-Christoph, Bernstein, Richard A, Cordonnier, Charlotte, Kahl, Anja, Abelian, Grigor, Donovan, Mark, Pachai, Chahin, Li, Danshi, and Hankey, Graeme J

Published
2024
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45. Goal Reasoning by Selecting Subgoals with Deep Q-Learning

Author

Núñez-Molina, Carlos, Nikolov, Vladislav, Vellido, Ignacio, and Fernández-Olivares, Juan

Subjects
Computer Science - Artificial Intelligence, I.2.8, I.2.6
Abstract

In this work we propose a goal reasoning method which learns to select subgoals with Deep Q-Learning in order to decrease the load of a planner when faced with scenarios with tight time restrictions, such as online execution systems. We have designed a CNN-based goal selection module and trained it on a standard video game environment, testing it on different games (planning domains) and levels (planning problems) to measure its generalization abilities. When comparing its performance with a satisfying planner, the results obtained show both approaches are able to find plans of good quality, but our method greatly decreases planning time. We conclude our approach can be successfully applied to different types of domains (games), and shows good generalization properties when evaluated on new levels (problems) of the same game (domain).

Published
2020

46. Intensive 90-day textile wearable Holter monitoring: an alternative to detect paroxysmal atrial fibrillation in selected patients with cryptogenic stroke

Author

Pagola, Jorge, Juega, Jesus, Francisco-Pascual, Jaume, Rodriguez, Maite, Dorado, Laura, Martinez, Raquel, De Lera-Alfonso, Mercedes, Arenillas, Juan F., Cabezas, Juan Antonio, Moniche, Francisco, de Torres, Reyes, Montaner, Joan, Muchada, Marian, Boned, Sandra, Requena, Manuel, García-Tornel, Alvaro, Rodríguez-Villatoro, Noelia, Rodríguez-Luna, David, Deck, Matías, Olivé, Marta, Rubiera, Marta, Ribó, Marc, Alvarez-Sabin, Jose, and Molina, Carlos A.

Published
2023
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