Obesity Prediction with EHR Data: A deep learning approach with interpretable elements M Gupta, TLT Phan, HT Bunnell, R Beheshti ACM Transactions on Computing for Healthcare (HEALTH) 3 (3), 1-19, 2022 | 54 | 2022 |
Concurrent Imputation and Prediction on EHR data using Bi-Directional GANs: Bi-GANs for EHR imputation and prediction M Gupta, TLT Phan, HT Bunnell, R Beheshti Proceedings of the 12th ACM Conference on Bioinformatics, Computational …, 2021 | 34* | 2021 |
An Extensive Data Processing Pipeline for MIMIC-IV M Gupta, B Gallamoza, N Cutrona, P Dhakal, R Poulain, R Beheshti Proceedings of the 2nd Machine Learning for Health symposium 193, 311--325, 2022 | 25 | 2022 |
Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records R Poulain, M Gupta, R Beheshti Machine Learning for Health Conference, 2022 | 10 | 2022 |
Transformer-based multi-target regression on electronic health records for primordial prevention of cardiovascular disease R Poulain, M Gupta, R Foraker, R Beheshti 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2021 | 8 | 2021 |
Transforming Relational Database to Graph Database Using Neo4j MG Rinkle Rani Aggarwal Proceedings of the Second International Conference on Emerging Research in …, 2014 | 5* | 2014 |
Flexible-Window Predictions on Electronic Health Records M Gupta, R Poulain, TLT Phan, HT Bunnell, R Beheshti Proceedings of the AAAI Conference on Artificial Intelligence 36, 12510-12516, 2022 | 4 | 2022 |
Reliable prediction of childhood obesity using only routinely collected EHRs is possible M Gupta, TLT Phan, D Eckrich, HT Bunnell, R Beheshti medRxiv, 2024.01. 29.24301945, 2024 | 1 | 2024 |
Associations of longitudinal BMI percentile classification patterns in early childhood with neighborhood-level social determinants of health M Gupta, TLT Phan, F Lê-Scherban, D Eckrich, HT Bunnell, R Beheshti medRxiv, 2023 | 1 | 2023 |
Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2022 Symposium S Hegselmann, H Zhou, Y Zhou, J Chien, S Nagaraj, N Hulkund, S Bhave, ... | | 2023 |