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1,715 results on '"Tabrizi, Reza"'

6. Isatuximab, lenalidomide, dexamethasone and bortezomib in transplant-ineligible multiple myeloma: the randomized phase 3 BENEFIT trial

Author

Leleu, Xavier, Hulin, Cyrille, Lambert, Jerome, Bobin, Arthur, Perrot, Aurore, Karlin, Lionel, Roussel, Murielle, Montes, Lydia, Cherel, Brieuc, Chalopin, Thomas, Slama, Borhane, Chretien, Marie-Lorraine, Laribi, Kamel, Dingremont, Claire, Roul, Christophe, Mariette, Clara, Rigaudeau, Sophie, Calmettes, Claire, Dib, Mamoun, Tiab, Mourad, Vincent, Laure, Delaunay, Jacques, Santagostino, Alberto, Macro, Margaret, Bourgeois, Emmanuelle, Orsini-Piocelle, Frederique, Gay, Julie, Bareau, Benoit, Bigot, Noemie, Vergez, François, Lebreton, Pierre, Tabrizi, Reza, Waultier-Rascalou, Agathe, Frenzel, Laurent, Le Calloch, Ronan, Chalayer, Emilie, Braun, Thorsten, Lachenal, Florence, Corm, Selim, Kennel, Celine, Belkhir, Rakiba, Bladé, Jean-Sebastien, Joly, Bertrand, Richez-Olivier, Valentine, Gardeney, Helene, Demarquette, Helene, Robu-Cretu, Daniela, Garderet, Laurent, Newinger-Porte, Muriel, Kasmi, Amine, Royer, Bruno, Decaux, Olivier, Arnulf, Bertrand, Belhadj, Karim, Touzeau, Cyrille, Mohty, Mohamad, Manier, Salomon, Moreau, Philippe, Avet-Loiseau, Hervé, Corre, Jill, and Facon, Thierry

Published
2024
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35. Sentiment Analysis Based on Smart Human Mobility: A Comparative Study of ML Models

Author

Rosa, Luís, Faria, Hugo, Tabrizi, Reza, Gonçalves, Simão, Silva, Fábio, Analide, Cesar, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ferrández Vicente, José Manuel, editor, Álvarez-Sánchez, José Ramón, editor, de la Paz López, Félix, editor, and Adeli, Hojjat, editor

Published
2022
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46. The Hospitalization Rate of Cerebral Venous Sinus Thrombosis before and during COVID-19 Pandemic Era: A Single-Center Retrospective Cohort Study

Author

Vasaghi Gharamaleki, Maryam, Habibagahi, Maryam, Hooshmandi, Etrat, Tabrizi, Reza, Arsang-Jang, Shahram, Barzegar, Zohreh, Fadakar, Nima, Reza Ostovan, Vahid, Rahimi-Jaberi, Abbas, Ashjazadeh, Nahid, Petramfar, Peyman, Poursadeghfard, Maryam, Izadi, Sadegh, Nazeri, Masoumeh, Bazrafshan, Hanieh, Bahrami, Zahra, Karimlu, Sedigheh, Shaghayegh Zafarmand, Seyedeh, Bayat, Mahnaz, Saied Salehi, Mohammad, Owjfard, Maryam, Karimi-Haghighi, Saeideh, Safari, Anahid, Shakibajahromi, Banafsheh, Lim Alvin Chew, Beng, Worral, Bradford B. g, Coutinho, Jonathan M., Garcia-Esperon, Carlos, Spratt, Neil, Levi, Christopher, Azarpazhooh, Mahmoud Reza, and Borhani-Haghighi, Afshin

Published
2022
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47. Bone expansion as a horizontal alveolar ridge augmentation technique: a systematic review and meta-analysis.

Author

Azadi, Ali, Hazrati, Parham, Tizno, Ashkan, Rezaei, Fatemeh, Akbarzadeh Baghban, Alireza, and Tabrizi, Reza

Abstract

Purpose: Bone expansion is one of the quickest, simplest, and most reliable methods of alveolar ridge augmentation for implant placement. This systematic review is designed to investigate the outcomes of the bone expansion technique for horizontal ridge augmentation. Methods: The protocol of study has been prospectively registered into PROSPERO (CRD42023414686). Pubmed, Embase, Web of Science, and Scopus databases were searched. Human original articles utilizing different bone expansion procedures for horizontal ridge augmentation without the use of bone materials or combined with vertical ridge augmentation techniques were included in the study. Qualitative and quantitative synthesis have been conducted. I-squared was used to assess heterogeneity. Meta-regression, forest plots random-effect model, and weighted mean difference were used for analysis. Leave-one-out influence analysis for finding outliers. Egger’s publication bias test and Funnel plots were used to address publication bias. Results: 3291 records were identified. Ten articles were included in this study after screening. The survival and complication rates of implants placed simultaneously with bone expansion was 100% 100% (95% CI: 99-100%) and 0% (95% CI: 0-1%), respectively. The meta-regression revealed that by each month passing from the implant placement the survival probability would be decreased significantly by 0.08% (95% CI: 0.009–0.15%; P = 0.03). The weighted mean ridge width difference before and after the osseodensification was 1.55 mm (95% CI: 0.92–2.17 mm). Conclusion: Based on the study’s limitations it can be concluded that the bone expansion procedure can be considered an efficient and safe method regarding the survival and complication rates of placed implants. Trial registration number: N/A. [ABSTRACT FROM AUTHOR]

Published
2025
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48. Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients.

Author

Andishgar, Aref, Bazmi, Sina, Lankarani, Kamran B., Taghavi, Seyed Alireza, Imanieh, Mohammad Hadi, Sivandzadeh, Gholamreza, Saeian, Samira, Dadashpour, Nazanin, Shamsaeefar, Alireza, Ravankhah, Mahdi, Deylami, Hamed Nikoupour, Tabrizi, Reza, and Imanieh, Mohammad Hossein

Subjects
MACHINE learning, FEATURE selection, MORTALITY risk factors, SURVIVAL rate, SURVIVAL analysis (Biometry)
Abstract

Post-Liver transplantation (LT) survival rates stagnate, with biliary complications (BC) as a major cause of death. We analyzed longitudinal data with a median 19-month follow-up. BC was diagnosed with ultrasounds and MRCP. Missing data was imputed using mean and median. Data preprocessing involved feature scaling and one-hot encoding. Survival analysis used filter (Cox-P, Cox-c) and embedded (RSF, LASSO) feature selection methods. Seven survival machine learning algorithms were used: LASSO, Ridge, RSF, E-NET, GBS, C-GBS, and FS-SVM. Model development employed 5-fold cross-validation, random oversampling, and hyperparameter tuning. Random oversampling addressed data imbalance. Optimal hyperparameters were determined based on average C-index. Features importance was assessed using standardized regression coefficients and permutation importance for top models. Stability was evaluated using 5-fold cross-validation standard deviation. Finally, 1799 observations with 40 outcome predictors were included. RSF with Ridge achieved the highest performance (C-index: 0.699) for BC prediction, while RSF with RSF had the highest performance (C-index: 0.784) for mortality prediction. Top BC predictors were LT graft types, IBD in recipients, recipient's BMI, recipient's history of PVT, and previous LT history. For mortality, they were post-transplant AST, creatinine, recipient's age, post-transplant ALT, and tacrolimus consumption. We identified BC and mortality risk factors, improving decision-making and outcomes. [ABSTRACT FROM AUTHOR]

Published
2025
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