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Scopus Author ID: 55619059000

Keywords

Machine Learning, Artificial Intelligence, Obesity, Electronic Health Records, Health Data Science

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Employment (1)

University of Delaware: Newark, DE, US

Assistant Professor (Computer & Information Sciences )
Employment
Source: Self-asserted source
Rahmatollah Beheshti

Education and qualifications (2)

University of Central Florida: Orlando, FL, US

PhD (Computer Science)
Education
Source: Self-asserted source
Rahmatollah Beheshti

Johns Hopkins University Bloomberg School of Public Health: Baltimore, MD, US

Post-Doctoral Fellow
Education
Source: Self-asserted source
Rahmatollah Beheshti

Works (50 of 51)

Items per page:
Page 1 of 2

Impact of COVID-19 Diagnosis on Weight Trajectories of Children in the US National COVID Cohort Collaborative

Childhood Obesity
2025-01-06 | Journal article | Author
DOI: 10.1089/chi.2024.0256
Part of ISSN: 2153-2168
Part of ISSN: 2153-2176
Contributors: Md Mozaharul Mottalib; Thao-Ly T. Phan; Carolyn T. Bramante; Christopher G. Chute; Lee A. Pyles; Rahmatollah Beheshti; On behalf of N3C
Source: Self-asserted source
Rahmatollah Beheshti

An Interoperable Machine Learning Pipeline for Pediatric Obesity Risk Estimation

Machine Learning for Health Symposium
2024 | Conference paper
DOI: 10.48550/ARXIV.2412.10454
Contributors: Hamed Fayyaz; Mehak Gupta; Alejandra Perez Ramirez; Claudine Jurkovitz; H. Timothy Bunnell; Thao-Ly T. Phan; Rahmatollah Beheshti
Source: Self-asserted source
Rahmatollah Beheshti

Bias patterns in the application of LLMs for clinical decision support: A comprehensive study

2024 | Journal article
DOI: 10.48550/ARXIV.2404.15149
Contributors: Raphael Poulain; Hamed Fayyaz; Rahmatollah Beheshti
Source: Self-asserted source
Rahmatollah Beheshti

Fairness-Optimized Synthetic EHR Generation for Arbitrary Downstream Predictive Tasks

2024 | Preprint
DOI: 10.48550/ARXIV.2406.02510
Contributors: Mirza Farhan Bin Tarek; Raphael Poulain; Rahmatollah Beheshti
Source: Self-asserted source
Rahmatollah Beheshti

Graph Transformers on EHRs: Better Representation Improves Downstream Performance

International Conference on Learning Representations (ICLR)
2024 | Journal article
Contributors: Poulain, Raphael; Beheshti, Rahmatollah
Source: Self-asserted source
Rahmatollah Beheshti

HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks

The IEEE/ACM international conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)
2024 | Conference paper
DOI: 10.48550/ARXIV.2403.18128
Contributors: Fahmida Liza Piya; Mehak Gupta; Rahmatollah Beheshti
Source: Self-asserted source
Rahmatollah Beheshti

Reliable prediction of childhood obesity using only routinely collected EHRs may be possible

Obesity Pillars
2024-12 | Journal article | Author
DOI: 10.1016/j.obpill.2024.100128
Part of ISSN: 2667-3681
PMID: 39315061
Contributors: Mehak Gupta; Daniel Eckrich; H Timothy Bunnell; Thao-Ly Tam Phan; Rahmatollah Beheshti
Source: Self-asserted source
Rahmatollah Beheshti

Associations of Longitudinal BMI-Percentile Classification Patterns in Early Childhood with Neighborhood-Level Social Determinants of Health

Childhood Obesity
2024-08-26 | Journal article | Author
DOI: 10.1089/chi.2023.0157
Part of ISSN: 2153-2168
Part of ISSN: 2153-2176
Contributors: Mehak Gupta; Thao-Ly T. Phan; Félice Lê-Scherban; Daniel Eckrich; H. Timothy Bunnell; Rahmatollah Beheshti
Source: Self-asserted source
Rahmatollah Beheshti

Associations of longitudinal BMI percentile classification patterns in early childhood with neighborhood-level social determinants of health

medRxiv
2023 | Journal article
Contributors: Gupta, Mehak; Phan, Thao-Ly T; L̂e-Scherban, Félice; Eckrich, Daniel; Bunnell, H Timothy; Beheshti, Rahmatollah
Source: Self-asserted source
Rahmatollah Beheshti

Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer Approach

Machine Learning for Healthcare
2023 | Journal article
Contributors: Fayyaz, Hamed; Beheshti, Rahmatollah
Source: Self-asserted source
Rahmatollah Beheshti

Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods

ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
2023 | Conference paper
DOI: 10.1145/3593013.3594102
Contributors: Raphael Poulain; Mirza Farhan Bin Tarek; Rahmatollah Beheshti
Source: Self-asserted source
Rahmatollah Beheshti
grade
Preferred source (of 2)‎

Subtyping Patients With Chronic Disease Using Longitudinal BMI Patterns

IEEE Journal of Biomedical and Health Informatics
2023 | Journal article
DOI: 10.1109/JBHI.2023.3237753
Contributors: Mottalib, Md Mozaharul; Jones-Smith, Jessica C; Sheridan, Bethany; Beheshti, Rahmatollah
Source: Self-asserted source
Rahmatollah Beheshti

An Extensive Data Processing Pipeline for MIMIC-IV

arXiv
2022 | Other
DOI: 10.48550/arXiv.2204.13841
EID:

2-s2.0-85130467156

Part of ISSN: 23318422
Contributors: Gupta, M.; Gallamoza, B.; Cutrona, N.; Dhakal, P.; Poulain, R.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

An Extensive Data Processing Pipeline for MIMIC-IV

Proceedings of the 2nd Machine Learning for Health symposium
2022 | Conference paper
Contributors: Gupta, Mehak; Gallamoza, Brennan; Cutrona, Nicolas; Dhakal, Pranjal; Poulain, Raphael; Beheshti, Rahmatollah
Source: Self-asserted source
Rahmatollah Beheshti

Developing Acute Event Risk Profiles for Older Adults with Dementia in Long-Term Care Using Motor Behavior Clusters Derived from Deep Learning

Journal of the American Medical Directors Association
2022 | Journal article
DOI: 10.1016/j.jamda.2022.04.009
EID:

2-s2.0-85135958798

Part of ISSN: 15389375 15258610
Contributors: Ramazi, R.; Bowen, M.E.L.; Flynn, A.J.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records

Machine Learning for Healthcare, PMLR 182:853-873
2022 | Conference paper
Contributors: Poulain, Raphael; Gupta, Mehak; Beheshti, Rahmatollah
Source: Self-asserted source
Rahmatollah Beheshti

Predicting Acute Events using the Movement Patterns of Older Adults: An Unsupervised Clustering Method

Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2022
2022 | Conference paper
DOI: 10.1145/3535508.3545561
EID:

2-s2.0-85137358454
Contributors: Ramazi, R.; Bowen, M.E.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Predicting attrition patterns from pediatric weight management programs

Proceedings of the 2nd Machine Learning for Health symposium
2022 | Conference paper
Contributors: Fayyaz, Hamed; Phan, Thao-Ly T.; Bunnell, H. Timothy; Beheshti, Rahmatollah
Source: Self-asserted source
Rahmatollah Beheshti

Who will Leave a Pediatric Weight Management Program and When? - A machine learning approach for predicting attrition patterns

arXiv
2022 | Other
EID:

2-s2.0-85124782170

Part of ISSN: 23318422
Contributors: Fayyaz, H.; Phan, T.-L.T.; Bunnell, H.T.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Obesity Prediction with EHR Data: A Deep Learning Approach with Interpretable Elements

ACM Transactions on Computing for Healthcare
2022-07-31 | Journal article | Author
DOI: 10.1145/3506719
Part of ISSN: 2691-1957
Part of ISSN: 2637-8051
Contributors: Mehak Gupta; Thao-Ly T. Phan; H. Timothy Bunnell; Rahmatollah Beheshti
Source: Self-asserted source
Rahmatollah Beheshti

Flexible-Window Predictions on Electronic Health Records

Proceedings of the AAAI Conference on Artificial Intelligence
2022-06-28 | Journal article
DOI: 10.1609/aaai.v36i11.21520
Part of ISSN: 2374-3468
Part of ISSN: 2159-5399
Contributors: Mehak Gupta; Raphael Poulain; Thao-Ly T. Phan; H. Timothy Bunnell; Rahmatollah Beheshti
Source: Self-asserted source
Rahmatollah Beheshti

Concurrent imputation and prediction on EHR data using bi-directional GANs: Bi-GANs for EHR imputation and prediction

Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB 2021
2021 | Conference paper
DOI: 10.1145/3459930.3469512
EID:

2-s2.0-85109562239
Contributors: Gupta, M.; Phan, T.-L.T.; Timothy Bunnell, H.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Identifying the leading factors of significant weight gains using a new rule discovery method

arXiv
2021 | Other
EID:

2-s2.0-85119573790

Part of ISSN: 23318422
Contributors: Samizadeh, M.; Jones-Smith, J.C.; Sheridan, B.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Identifying the risks of chronic diseases using BMI trajectories

arXiv
2021 | Other
EID:

2-s2.0-85119574513

Part of ISSN: 23318422
Contributors: Mottalib, M.M.; Jones-Smith, J.C.; Sheridan, B.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models

BMC Medical Informatics and Decision Making
2021 | Journal article
DOI: 10.1186/s12911-020-01345-1
EID:

2-s2.0-85098760575

Part of ISSN: 14726947
Contributors: Guo, A.; Beheshti, R.; Khan, Y.M.; Langabeer, J.R.; Foraker, R.E.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Predicting progression patterns of type 2 diabetes using multi-sensor measurements

Smart Health
2021 | Journal article
DOI: 10.1016/j.smhl.2021.100206
EID:

2-s2.0-85109540633

Part of ISSN: 23526483
Contributors: Ramazi, R.; Perndorfer, C.; Soriano, E.C.; Laurenceau, J.-P.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Transformer-based Multi-target Regression on Electronic Health Records for Primordial Prevention of Cardiovascular Disease

Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
2021 | Conference paper
DOI: 10.1109/BIBM52615.2021.9669441
EID:

2-s2.0-85125184620
Contributors: Poulain, R.; Gupta, M.; Foraker, R.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Time-series imputation and prediction with bi-directional generative adversarial networks

arXiv
2020 | Other
EID:

2-s2.0-85098398958

Part of ISSN: 23318422
Contributors: Gupta, M.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Multi-modal predictive models of diabetes progression

ACM-BCB 2019 - Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
2019 | Conference paper
DOI: 10.1145/3307339.3342177
EID:

2-s2.0-85073156795
Contributors: Ramazi, R.; Perndorfer, C.; Soriano, E.; Laurenceau, J.-P.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Multi-modal Predictive Models of Diabetes Progression

arXiv
2019 | Other
EID:

2-s2.0-85094299304

Part of ISSN: 23318422
Contributors: Ramazi, R.; Laurenceau, J.-P.; Perndorfer, C.; Soriano, E.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Obesity prediction with EHR data: A deep learning approach with interpretable elements

arXiv
2019 | Other
EID:

2-s2.0-85119114202

Part of ISSN: 23318422
Contributors: Gupta, M.; Phan, T.-L.T.; Bunnell, H.T.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Using agent-based models to understand health-related social norms

Social-Behavioral Modeling for Complex Systems
2019 | Book chapter
Part of DOI: 10.1002/9781119485001.ch27
EID:

2-s2.0-85102547537
Contributors: Sukthankar, G.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

A predictive model of rat calorie intake as a function of diet energy density

American Journal of Physiology - Regulatory Integrative and Comparative Physiology
2018 | Journal article
DOI: 10.1152/ajpregu.00337.2017
EID:

2-s2.0-85051510645

Part of ISSN: 15221490 03636119
Contributors: Beheshti, R.; Treesukosol, Y.; Igusa, T.; Moran, T.H.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

A predictive model of rats' calorie intake as a function of diet energy density

bioRxiv
2017 | Other
DOI: 10.1101/184085
EID:

2-s2.0-85093379250

Part of ISSN: 26928205
Contributors: Beheshti, R.; Treesukosol, Y.; Igusa, T.; Moran, T.H.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Comparing methods of targeting obesity interventions in populations: An agent-based simulation

SSM - Population Health
2017 | Journal article
DOI: 10.1016/j.ssmph.2017.01.006
EID:

2-s2.0-85011890862

Part of ISSN: 23528273
Contributors: Beheshti, R.; Jalalpour, M.; Glass, T.A.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Taking dietary habits into account: A Computational method for modeling food choices that goes beyond price

PLoS ONE
2017 | Journal article
DOI: 10.1371/journal.pone.0178348
EID:

2-s2.0-85019737620

Part of ISSN: 19326203
Contributors: Beheshti, R.; Jones-Smith, J.C.; Igusa, T.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Negotiations in holonic multi-agent systems

Studies in Computational Intelligence
2016 | Book
DOI: 10.1007/978-3-319-30307-9_7
EID:

2-s2.0-84962261959

Part of ISSN: 1860949X
Contributors: Beheshti, R.; Barmaki, R.; Mozayani, N.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Simulated models suggest that price per calorie is the dominant price metric that low-income individuals use for food decision making

Journal of Nutrition
2016 | Journal article
DOI: 10.3945/jn.116.235952
EID:

2-s2.0-84995481316

Part of ISSN: 15416100 00223166
Contributors: Beheshti, R.; Igusa, T.; Jones-Smith, J.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

A hybrid modeling approach for parking and traffic prediction in urban simulations

AI and Society
2015 | Journal article
DOI: 10.1007/s00146-013-0530-7
EID:

2-s2.0-84938970769

Part of ISSN: 14355655 09515666
Contributors: Beheshti, R.; Sukthankar, G.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Modeling implicit collaboration with normative agent architectures

2015 International Conference on Collaboration Technologies and Systems, CTS 2015
2015 | Conference paper
DOI: 10.1109/CTS.2015.7210406
EID:

2-s2.0-84959552665
Contributors: Sukthankar, G.; Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Modeling tipping point theory using normative multi-agent systems

Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
2015 | Conference paper
EID:

2-s2.0-84944705450

Part of ISSN: 15582914 15488403
Contributors: Beheshti, R.; Sukthankar, G.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Cognitive Social Learners: An Architecture for Modeling Normative Behavior

Proceedings of the AAAI Conference on Artificial Intelligence
2015-02-18 | Journal article
DOI: 10.1609/aaai.v29i1.9441
Part of ISSN: 2374-3468
Part of ISSN: 2159-5399
Contributors: Rahmatollah Beheshti; Awrad Mohammed Ali; Gita Sukthankar
Source: Self-asserted source
Rahmatollah Beheshti

A normative agent-based model for predicting smoking cessation trends

13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
2014 | Conference paper
EID:

2-s2.0-84911412771
Contributors: Beheshti, R.; Sukthankar, G.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

HOMAN, a learning based negotiation method for holonic multi-agent systems

Journal of Intelligent and Fuzzy Systems
2014 | Journal article
DOI: 10.3233/IFS-120757
EID:

2-s2.0-84892925605

Part of ISSN: 10641246 18758967
Contributors: Beheshti, R.; Mozayani, N.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Normative agents for real-world scenarios

13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
2014 | Conference paper
EID:

2-s2.0-84911440202
Contributors: Beheshti, R.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Analyzing agent-based models using category theory

Proceedings - 2013 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2013
2013 | Conference paper
DOI: 10.1109/WI-IAT.2013.121
EID:

2-s2.0-84893251238
Contributors: Beheshti, R.; Sukthankar, G.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Improving Markov chain Monte Carlo estimation with agent-based models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2013 | Book
DOI: 10.1007/978-3-642-37210-0_54
EID:

2-s2.0-84874814870

Part of ISSN: 03029743 16113349
Contributors: Beheshti, R.; Sukthankar, G.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

Extracting agent-based models of human transportation patterns

Proceedings of the 2012 ASE International Conference on Social Informatics, SocialInformatics 2012
2012 | Conference paper
DOI: 10.1109/SocialInformatics.2012.60
EID:

2-s2.0-84881055818
Contributors: Beheshti, R.; Sukthankar, G.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

A new mechanism for negotiations in multi-agent systems based on ARTMAP artificial neural network

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2011 | Book
DOI: 10.1007/978-3-642-22000-5_33
EID:

2-s2.0-79960302620

Part of ISSN: 03029743 16113349
Contributors: Beheshti, R.; Mozayani, N.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier

A multi-objective genetic algorithm method to support multi-agent negotiations

2009 2nd International Conference on Future Information Technology and Management Engineering, FITME 2009
2009 | Conference paper
DOI: 10.1109/FITME.2009.154
EID:

2-s2.0-77950912416
Contributors: Beheshti, R.; Rahmani, A.T.
Source: Self-asserted source
Rahmatollah Beheshti via Scopus - Elsevier
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