Submitted

Tu Do, Mehak Gupta, Joshua R. Oltmanns (2025). “Racial Disparities in Personality Assessment using Language Models”. Manuscript under review.[cite: 1]
D Owens, E D Peterson, Mehak Gupta, DQ Nguyen, M Dohopolski, J Cao, A M Navar (2025). “Ensemble-Guided Selective Application of Large Language Models”. Manuscript under review.[cite: 1]
T Li, Rasiq Hussain, Mehak Gupta, Joshua R. Oltmanns (2025). “‘Mirror’ Language AI Models of Depression are Criterion-Contaminated”. Manuscript under review.[cite: 1]

Journal Papers

D Owens, E D Peterson, Mehak Gupta, DQ Nguyen, M Dohopolski, J Cao, A M Navar. “Targeted use of large language models for EHR-based computable phenotyping”. Journal of the American Medical Informatics Association. DOI: 10.1093/jamia/ocag051.[cite: 1]
Rasiq Hussain, Jerry Ma, Ritik Khandelwal, Joshua R. Oltmanns, Mehak Gupta. “Language-Based Personality Assessment from Life Narratives: A Focus on Model Interpretability and Efficiency”. Frontiers in Artificial Intelligence.[cite: 1]

Joshua R. Oltmanns, Ritik Khandelwal, Jerry Ma, Jocelyn Brickman, Tu Do, Rasiq Hussain, and Mehak Gupta. “Language-based AI Modeling of Personality Traits and Pathology from Life Narrative Interviews”. Journal of Psychopathology and Clinical Science, Vol. 135, Issue 1, pp. 122-135. DOI: 10.1037/abn0001047.[cite: 1]
Nahed Abdelgaber, Labiba Jahan, Joshua R. Oltmanns, Mehak Gupta, and Jia Zhang. “Interpretable Socioeconomic Profiling: A Deep Dive Beyond Narrative Classification”. Journal of Data Mining & Digital Humanities. DOI: 10.46298/jdmdh.16258.[cite: 1]
Jocelyn Brickman, Mehak Gupta, and Joshua R. Oltmanns. “Large Language Models for Psychological Assessment: A Comprehensive Overview”. Advances in Methods and Practices in Psychological Science, Vol. 8, Issue 3. DOI: 10.1177/25152459251343582.[cite: 1]

Mehak Gupta, Thao-Ly T Phan, F´elice Lˆe-Scherban, Daniel Eckrich, H Timothy Bunnell and Rahmatollah Beheshti. “Associations of Longitudinal BMI-Percentile Classification Patterns in Early Childhood with Neighborhood- Level Social Determinants of Health”. Childhood Obesity 2024 Aug 26; PubMed PMID: 39187268. (View)
Mehak Gupta, Thao-Ly T Phan, Daniel Eckrich, H Timothy Bunnell and Rahmatollah Beheshti “Obesity prediction with ehr data: A deep learning approach with interpretable elements”. Obesity Pillars. 2024 September 10; :100128. DOI: 10.1016/j.obpill.2024.100128. (View)

Mehak Gupta, Thao-Ly T Phan, H Timothy Bunnell, and Rahmatollah Beheshti. “Obesity prediction with ehr data: A deep learning approach with interpretable elements”. ACM Transactions on Computing for Healthcare (HEALTH), 3(3):1–19, 2022 (View)

Nikkie Hooman, Zhongjie Wu, Eric C. Larson, and Mehak Gupta. “Multimodal Routing for Interpretable, Robust, and Auditable Clinical Prediction”. IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).[cite: 1]

Nikkie Hooman, Zhongjie Wu, Eric C. Larson, and Mehak Gupta. “Equitable Electronic Health Record Prediction with FAME: Fairness-Aware Multimodal Embedding”. In Proceedings of the 10th Machine Learning for Healthcare Conference, Vol. 298, PMLR.[cite: 1]
Nahed Abdelgaber, Labiba Jahan, Nino Castellano, Joshua Oltmanns, Mehak Gupta, Jia Zhang, Akshay Pednekar, Ashish Basavaraju, Ian Velazquez, and Zerui Ma. “AI Assistant for Socioeconomic Empowerment Using Federated Learning”. In Proceedings of the 5th International Conference on Natural Language Processing for Digital Humanities, pp. 490-501.[cite: 1]

Hamed Fayyaz, Mehak Gupta, Alejandra Perez Ramirez, Claudine Jurkovitz, H. Timothy Bunnell, Thao-Ly T. Phan, and Rahmatollah Beheshti. “An Interoperable Machine Learning Pipeline for Pediatric Obesity Risk Estimation”. Proceedings of Machine Learning Research, Vol. 259, pp. 308.[cite: 1]
Fahmida Liza Piya, Mehak Gupta and Rahmatollah Beheshti. “HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks”. IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) (View)

Mehak Gupta, Brennan Gallamoza, Nicolas Cutrona, Pranjal Dhakal, Raphael Poulain, and Rahmatollah Beheshti. “An Extensive Data Processing Pipeline for MIMIC-IV”. In Proceedings of the 2nd Machine Learning for Health symposium, volume 193 of Proceedings of Machine Learning Research, pages 311–325. PMLR. 2022 (View)
Raphael Poulain, Mehak Gupta, and Rahmatollah Beheshti. “Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records.”. Machine Learning for Healthcare Conference, pages 1–21, 2022. (View)

Gupta, M., Poulain, R., T. Phan, T.-L., Bunnell, H. T. and Beheshti, R. “Flexible-window Predictions on Electronic Health Records”. In Proceedings of the AAAI Conference on Artificial Intelligence, 36(11):12510-12516. (IAAI-Track) (View)
Poulain, R., Gupta, M., Foraker, R. and Beheshti, R. “Transformer-based Multi-target Regression on Electronic Health Records for Primordial Prevention of Cardiovascular Disease”. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (View)
Gupta, M., T. Phan, T.-L., Bunnell, H. T. and Beheshti, R. “Concurrent Imputation and Prediction on EHR data using Bi-Directional GANs”. In Proceedings of the 12th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. (View)

Gupta, M. and Aggarwal, R.. “Transforming Relational Database to Graph Database Using Neo4j”, In Proceedings of the Second International Conference on Emerging Research in Computing, Information, Communication and Applications, Bangalore, India.