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 | 61 | 2022 |
Comparing methods of targeting obesity interventions in populations: an agent-based simulation R Beheshti, M Jalalpour, TA Glass SSM-population health 3, 211-218, 2017 | 39 | 2017 |
A hybrid modeling approach for parking and traffic prediction in urban simulations R Beheshti, G Sukthankar AI & society 30, 333-344, 2015 | 34 | 2015 |
An extensive data processing pipeline for MIMIC-IV M Gupta, B Gallamoza, N Cutrona, P Dhakal, R Poulain, R Beheshti Machine Learning for Health, 311-325, 2022 | 30 | 2022 |
A normative agent-based model for predicting smoking cessation trends R Beheshti, G Sukthankar Proceedings of the 2014 international conference on Autonomous agents and …, 2014 | 29 | 2014 |
Simulated models suggest that price per calorie is the dominant price metric that low-income individuals use for food decision making R Beheshti, T Igusa, J Jones-Smith The Journal of nutrition 146 (11), 2304-2311, 2016 | 25 | 2016 |
Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models A Guo, R Beheshti, YM Khan, JR Langabeer, RE Foraker BMC medical informatics and decision making 21, 1-10, 2021 | 24 | 2021 |
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 | 22 | 2021 |
Extracting agent-based models of human transportation patterns R Beheshti, G Sukthankar 2012 International Conference on Social Informatics, 157-164, 2012 | 18 | 2012 |
Multi-modal predictive models of diabetes progression R Ramazi, C Perndorfer, E Soriano, JP Laurenceau, R Beheshti Proceedings of the 10th ACM International Conference on Bioinformatics …, 2019 | 17 | 2019 |
Cognitive social learners: An architecture for modeling normative behavior R Beheshti, AM Ali, G Sukthankar Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 17 | 2015 |
Time-series imputation and prediction with bi-directional generative adversarial networks M Gupta, R Beheshti arXiv preprint arXiv:2009.08900, 2020 | 16 | 2020 |
Taking dietary habits into account: A computational method for modeling food choices that goes beyond price R Beheshti, JC Jones-Smith, T Igusa PLoS One 12 (5), e0178348, 2017 | 15 | 2017 |
Improving fairness in AI models on electronic health records: The case for federated learning methods R Poulain, MF Bin Tarek, R Beheshti Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 14 | 2023 |
HOMAN, a learning based negotiation method for holonic multi-agent systems R Beheshti, N Mozayani Journal of Intelligent & Fuzzy Systems 26 (2), 655-666, 2014 | 11 | 2014 |
Few-shot learning with semi-supervised transformers for electronic health records R Poulain, M Gupta, R Beheshti Machine Learning for Healthcare Conference, 853-873, 2022 | 9 | 2022 |
A predictive model of rat calorie intake as a function of diet energy density R Beheshti, Y Treesukosol, T Igusa, TH Moran American Journal of Physiology-Regulatory, Integrative and Comparative …, 2018 | 9 | 2018 |
Normative agents for real-world scenarios R Beheshti Proceedings of the 2014 international conference on Autonomous agents and …, 2014 | 9 | 2014 |
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 |
Negotiations in holonic multi-agent systems R Beheshti, R Barmaki, N Mozayani Recent Advances in Agent-Based Complex Automated Negotiation, 107-118, 2016 | 8 | 2016 |