| Using deep learning to predict abdominal age from liver and pancreas magnetic resonance images A Le Goallec, S Diai, S Collin, JB Prost, T Vincent, CJ Patel Nature Communications 13 (1), 1979, 2022 | 29 | 2022 |
| Dissecting heart age using cardiac magnetic resonance videos, electrocardiograms, biobanks, and deep learning AL Goallec, JB Prost, S Collin, S Diai, T Vincent, CJ Patel medRxiv, 2021.06. 09.21258645, 2021 | 13 | 2021 |
| Analyzing the multidimensionality of biological aging with the tools of deep learning across diverse image-based and physiological indicators yields robust age predictors A Le Goallec, S Collin, S Diai, JB Prost, MH Jabri, T Vincent, CJ Patel medRxiv, 2021.04. 25.21255767, 2021 | 13 | 2021 |
| Deep learning of fundus and optical coherence tomography images enables identification of diverse genetic and environmental factors associated with eye aging A Le Goallec, S Diai, S Collin, T Vincent, CJ Patel medRxiv, 2021.06. 24.21259471, 2021 | 5* | 2021 |
| Predicting arterial age using carotid ultrasound images, pulse wave analysis records, cardiovascular biomarkers and deep learning A Le Goallec, S Collin, S Diai, T Vincent, CJ Patel medRxiv, 2021.06. 17.21259120, 2021 | 5 | 2021 |
| Using deep learning to analyze the compositeness of musculoskeletal aging reveals that spine, hip and knee age at different rates, and are associated with different genetic and … AL Goallec, S Diai, S Collin, T Vincent, CJ Patel medRxiv, 2021.06. 14.21258896, 2021 | 4 | 2021 |
| Machine learning approaches to predict age from accelerometer records of physical activity at biobank scale A Le Goallec, S Collin, MH Jabri, S Diai, T Vincent, CJ Patel PLOS Digital Health 2 (1), e0000176, 2023 | 3 | 2023 |
| Using deep learning to predict brain age from brain magnetic resonance images and cognitive tests reveals that anatomical and functional brain aging are phenotypically and … AL Goallec, S Diai, S Collin, T Vincent, CJ Patel medRxiv, 2021.06. 22.21259280, 2021 | 2 | 2021 |
| Adaptive -Network: On-the-fly Target Selection for Deep Reinforcement Learning T Vincent, F Wahren, J Peters, B Belousov, C D'Eramo arXiv preprint arXiv:2405.16195, 2024 | | 2024 |
| Parameterized projected Bellman operator T Vincent, AM Metelli, B Belousov, J Peters, M Restelli, C D'Eramo Proceedings of the AAAI Conference on Artificial Intelligence 38 (14), 15402 …, 2024 | | 2024 |
| Iterated -Network: Beyond the One-Step Bellman Operator T Vincent, D Palenicek, B Belousov, J Peters, C D'Eramo arXiv preprint arXiv:2403.02107, 2024 | | 2024 |
| Comparing the genetic and environmental architecture of blood count, blood biochemistry and urine biochemistry biological ages with machine learning A Le Goallec, S Diai, T Vincent, CJ Patel medRxiv, 2021.07. 05.21260032, 2021 | | 2021 |
| Predicting age from hearing test results with machine learning reveals the genetic and environmental factors underlying accelerated auditory aging AL Goallec, S Diai, T Vincent, CJ Patel medRxiv, 2021.07. 05.21260048, 2021 | | 2021 |
Chirag J PatelAssociate Professor of Biomedical Informatics, Harvard UniversityVerified email at hms.harvard.edu
