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Rahmatollah Beheshti
Person information
- affiliation: University of Delaware, USA
- affiliation: Johns Hopkins University, USA
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2020 – today
- 2024
- [c22]Fahmida Liza Piya, Mehak Gupta, Rahmatollah Beheshti:
HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks. CHASE 2024: 132-141 - [c21]Raphael Poulain, Rahmatollah Beheshti:
Graph Transformers on EHRs: Better Representation Improves Downstream Performance. ICLR 2024 - [i13]Hamed Fayyaz, Abigail Strang, Niharika Shimona D'Souza, Rahmatollah Beheshti:
Multimodal Sleep Apnea Detection with Missing or Noisy Modalities. CoRR abs/2402.17788 (2024) - [i12]Fahmida Liza Piya, Mehak Gupta, Rahmatollah Beheshti:
HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks. CoRR abs/2403.18128 (2024) - [i11]Raphael Poulain, Hamed Fayyaz, Rahmatollah Beheshti:
Bias patterns in the application of LLMs for clinical decision support: A comprehensive study. CoRR abs/2404.15149 (2024) - [i10]Mirza Farhan Bin Tarek, Raphael Poulain, Rahmatollah Beheshti:
Fairness-Optimized Synthetic EHR Generation for Arbitrary Downstream Predictive Tasks. CoRR abs/2406.02510 (2024) - [i9]Raphael Poulain, Hamed Fayyaz, Rahmatollah Beheshti:
Aligning (Medical) LLMs for (Counterfactual) Fairness. CoRR abs/2408.12055 (2024) - 2023
- [j6]Md Mozaharul Mottalib, Jessica C. Jones-Smith, Bethany Sheridan, Rahmatollah Beheshti:
Subtyping Patients With Chronic Disease Using Longitudinal BMI Patterns. IEEE J. Biomed. Health Informatics 27(4): 2083-2093 (2023) - [c20]Raphael Poulain, Mirza Farhan Bin Tarek, Rahmatollah Beheshti:
Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods. FAccT 2023: 1599-1608 - [c19]Hamed Fayyaz, Abigail Strang, Rahmatollah Beheshti:
Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer Approach. MLHC 2023: 167-185 - [i8]Raphael Poulain, Mirza Farhan Bin Tarek, Rahmatollah Beheshti:
Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods. CoRR abs/2305.11386 (2023) - 2022
- [j5]Mehak Gupta, Thao-Ly T. Phan, H. Timothy Bunnell, Rahmatollah Beheshti:
Obesity Prediction with EHR Data: A Deep Learning Approach with Interpretable Elements. ACM Trans. Comput. Heal. 3(3): 32:1-32:19 (2022) - [c18]Mehak Gupta, Raphael Poulain, Thao-Ly T. Phan, H. Timothy Bunnell, Rahmatollah Beheshti:
Flexible-Window Predictions on Electronic Health Records. AAAI 2022: 12510-12516 - [c17]Ramin Ramazi, Mary Elizabeth Bowen, Rahmatollah Beheshti:
Predicting acute events using the movement patterns of older adults: an unsupervised clustering method. BCB 2022: 19:1-19:9 - [c16]Mehak Gupta, Brennan Gallamoza, Nicolas Cutrona, Pranjal Dhakal, Raphael Poulain, Rahmatollah Beheshti:
An Extensive Data Processing Pipeline for MIMIC-IV. ML4H@NeurIPS 2022: 311-325 - [c15]Hamed Fayyaz, Thao-Ly T. Phan, H. Timothy Bunnell, Rahmatollah Beheshti:
Predicting attrition patterns from pediatric weight management programs. ML4H@NeurIPS 2022: 326-342 - [c14]Raphael Poulain, Mehak Gupta, Rahmatollah Beheshti:
Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records. MLHC 2022: 853-873 - [i7]Hamed Fayyaz, Thao-Ly T. Phan, H. Timothy Bunnell, Rahmatollah Beheshti:
Who will Leave a Pediatric Weight Management Program and When? - A machine learning approach for predicting attrition patterns. CoRR abs/2202.01765 (2022) - [i6]Mehak Gupta, Brennan Gallamoza, Nicolas Cutrona, Pranjal Dhakal, Raphael Poulain, Rahmatollah Beheshti:
An Extensive Data Processing Pipeline for MIMIC-IV. CoRR abs/2204.13841 (2022) - 2021
- [j4]Aixia Guo, Rahmatollah Beheshti, Yosef M. Khan, James R. Langabeer II, Randi E. Foraker:
Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models. BMC Medical Informatics Decis. Mak. 21(1): 5 (2021) - [c13]Mehak Gupta, Thao-Ly T. Phan, H. Timothy Bunnell, Rahmatollah Beheshti:
Concurrent imputation and prediction on EHR data using bi-directional GANs: Bi-GANs for EHR imputation and prediction. BCB 2021: 7:1-7:9 - [c12]Raphael Poulain, Mehak Gupta, Randi E. Foraker, Rahmatollah Beheshti:
Transformer-based Multi-target Regression on Electronic Health Records for Primordial Prevention of Cardiovascular Disease. BIBM 2021: 726-731 - [i5]Mina Samizadeh, Jessica C. Jones-Smith, Bethany Sheridan, Rahmatollah Beheshti:
Identifying the Leading Factors of Significant Weight Gains Using a New Rule Discovery Method. CoRR abs/2111.04475 (2021) - [i4]Md Mozaharul Mottalib, Jessica C. Jones-Smith, Bethany Sheridan, Rahmatollah Beheshti:
Identifying the Risks of Chronic Diseases Using BMI Trajectories. CoRR abs/2111.05385 (2021) - 2020
- [i3]Mehak Gupta, Rahmatollah Beheshti:
Time-series Imputation and Prediction with Bi-Directional Generative Adversarial Networks. CoRR abs/2009.08900 (2020)
2010 – 2019
- 2019
- [c11]Ramin Ramazi, Christine Perndorfer, Emily Soriano, Jean-Philippe Laurenceau, Rahmatollah Beheshti:
Multi-modal Predictive Models of Diabetes Progression. BCB 2019: 253-258 - [i2]Ramin Ramazi, Christine Perndorfer, Emily Soriano, Jean-Philippe Laurenceau, Rahmatollah Beheshti:
Multi-modal Predictive Models of Diabetes Progression. CoRR abs/1907.12175 (2019) - [i1]Mehak Gupta, Thao-Ly T. Phan, George Datto, H. Timothy Bunnell, Rahmatollah Beheshti:
Obesity Prediction with EHR Data: A deep learning approach with interpretability. CoRR abs/1912.02655 (2019) - 2015
- [j3]Rahmatollah Beheshti:
Modeling social norms in real-world agent-based simulations. AI Matters 2(1): 9-11 (2015) - [j2]Rahmatollah Beheshti, Gita Sukthankar:
A hybrid modeling approach for parking and traffic prediction in urban simulations. AI Soc. 30(3): 333-344 (2015) - [c10]Rahmatollah Beheshti, Awrad Mohammed Ali, Gita Reese Sukthankar:
Cognitive Social Learners: An Architecture for Modeling Normative Behavior. AAAI 2015: 2017-2023 - [c9]Rahmatollah Beheshti, Gita Sukthankar:
Modeling Tipping Point Theory using Normative Multi-agent Systems: (Extended Abstract). AAMAS 2015: 1731-1732 - [c8]Gita Sukthankar, Rahmatollah Beheshti:
Modeling implicit collaboration with normative agent architectures. CTS 2015: 489 - 2014
- [j1]Rahmatollah Beheshti, Nasser Mozayani:
HOMAN, a learning based negotiation method for holonic multi-agent systems. J. Intell. Fuzzy Syst. 26(2): 655-666 (2014) - [c7]Rahmatollah Beheshti, Roghayeh Barmaki, Nasser Mozayani:
Negotiations in Holonic Multi-agent Systems. ANAC@AAMAS 2014: 107-118 - [c6]Rahmatollah Beheshti, Gita Sukthankar:
A normative agent-based model for predicting smoking cessation trends. AAMAS 2014: 557-564 - [c5]Rahmatollah Beheshti:
Normative agents for real-world scenarios. AAMAS 2014: 1749-1750 - 2013
- [c4]Rahmatollah Beheshti, Gita Sukthankar:
Analyzing Agent-Based Models Using Category Theory. IAT 2013: 280-286 - [c3]Rahmatollah Beheshti, Gita Sukthankar:
Improving Markov Chain Monte Carlo Estimation with Agent-Based Models. SBP 2013: 495-502 - 2012
- [c2]Rahmatollah Beheshti, Gita Sukthankar:
Extracting Agent-Based Models of Human Transportation Patterns. SocialInformatics 2012: 157-164 - 2011
- [c1]Rahmatollah Beheshti, Nasser Mozayani:
A New Mechanism for Negotiations in Multi-Agent Systems Based on ARTMAP Artificial Neural Network. KES-AMSTA 2011: 311-320
Coauthor Index
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last updated on 2024-09-30 00:59 CEST by the dblp team
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