Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies.
Trans. Mach. Learn. Res., 2024
Dissecting Query-Key Interaction in Vision Transformers.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Training Recurrent Neural Network-Based Model to Predict COVID-19 Patient Risk for PASC using Pytorch_EHR - Hands-on Tutorial on N3C.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023
A Deep-Learning-based Two-Compartment Predictive Model (PKRNN-2CM) for Vancomycin Therapeutic Drug Monitoring.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023
Less is More: Reducing Overfitting in Deep Learning for EEG Classification.
Proceedings of the Computing in Cardiology, 2023
PK-RNN-V E: A deep learning model approach to vancomycin therapeutic drug monitoring using electronic health record data.
J. Biomed. Informatics, 2022
Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction.
npj Digit. Medicine, 2021
CovRNN: predicting outcomes of COVID-19 patients on admission using their electronic health records with minimal data processing.
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Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
Generalizable Gated Recurrent Neural Network based model to predict COVID-19 patient outcomes on admission.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction.
CoRR, 2020