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An explainable Transformer-based deep learning model for the prediction of incident heart failure.

S. Rao, Y. Li, R. Ramakrishnan, A. Hassaïne, D. Canoy, J. Cleland, T. Lukasiewicz, G. Khorshidi, and K. Rahimi. CoRR, (2021)

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Li Li

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Hi-BEHRT: Hierarchical Transformer-based model for accurate prediction of clinical events using multimodal longitudinal electronic health records.Y. Li, M. Mamouei, G. Khorshidi, S. Rao, A. Hassaïne, D. Canoy, T. Lukasiewicz, and K. Rahimi. CoRR, (2021)Risk factor identification for incident heart failure using neural network distillation and variable selection.Y. Li, S. Rao, M. Mamouei, G. Khorshidi, D. Canoy, A. Hassaïne, and T. Lukasiewicz. CoRR, (2021)Learning Multimorbidity Patterns from Electronic Health Records Using Non-negative Matrix Factorisation.A. Hassaïne, D. Canoy, J. Solares, Y. Zhu, S. Rao, Y. Li, K. Rahimi, and G. Khorshidi. CoRR, (2019)Hi-BEHRT: Hierarchical Transformer-Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records.Y. Li, M. Mamouei, G. Salimi-Khorshidi, S. Rao, A. Hassaïne, D. Canoy, T. Lukasiewicz, and K. Rahimi. IEEE J. Biomed. Health Informatics, 27 (2): 1106-1117 (February 2023)Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes.Y. Li, L. Yao, C. Mao, A. Srivastava, X. Jiang, and Y. Luo. BIBM, page 683-686. IEEE Computer Society, (2018)A Comparative Study of Pretrained Language Models for Long Clinical Text.Y. Li, R. Wehbe, F. Ahmad, H. Wang, and Y. Luo. CoRR, (2023)Deep Bayesian Gaussian Processes for Uncertainty Estimation in Electronic Health Records.Y. Li, S. Rao, A. Hassaïne, R. Ramakrishnan, Y. Zhu, D. Canoy, G. Khorshidi, T. Lukasiewicz, and K. Rahimi. CoRR, (2020)AD-BERT: Using pre-trained language model to predict the progression from mild cognitive impairment to Alzheimer's disease.C. Mao, J. Xu, L. Rasmussen, Y. Li, P. Adekkanattu, J. Pacheco, B. Bonakdarpour, R. Vassar, L. Shen, G. Jiang and 3 other author(s). J. Biomed. Informatics, (August 2023)AD-BERT: Using Pre-trained contextualized embeddings to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease.C. Mao, J. Xu, L. Rasmussen, Y. Li, P. Adekkanattu, J. Pacheco, B. Bonakdarpour, R. Vassar, G. Jiang, F. Wang and 2 other author(s). CoRR, (2022)Clinical outcome prediction under hypothetical interventions - a representation learning framework for counterfactual reasoning.Y. Li, M. Mamouei, S. Rao, A. Hassaïne, D. Canoy, T. Lukasiewicz, K. Rahimi, and G. Khorshidi. CoRR, (2022)

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Disambiguation of "Li, Yikuan"

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An explainable Transformer-based deep learning model for the prediction of incident heart failure.

Please choose a person to relate this publication to

Li Li

Li Li

Li Li

Li Li

Li Li

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Li, Yikuan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML An explainable Transformer-based deep learning model for the prediction of incident heart failure.

Please choose a person to relate this publication to

Li Li

Li Li

Li Li

Li Li

Li Li

Other publications of authors with the same name

Disambiguation

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An explainable Transformer-based deep learning model for the prediction of incident heart failure.