Dr. Marzyeh Ghassemi

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Citations	4274	4047
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i10-index	61	59

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Peter SzolovitsProfessor of Computer Science and Engineering, MITVerified email at mit.edu
Leo Anthony CeliMassachusetts Institute of TechnologyVerified email at mit.edu
Tristan NaumannPrincipal Researcher, Microsoft Research Health FuturesVerified email at microsoft.com
Matthew B. A. McDermottPhD Student, Massachusetts Institute of TechnologyVerified email at mit.edu
Anna GoldenbergScientist, SickKids Research Institute; Assistant Professor Department of Computer Science, University of TorontoVerified email at utoronto.ca
Irene Y. ChenPhD Student, MITVerified email at mit.edu
Joseph Paul CohenPostdoctoral Fellow, AIMI (Stanford University) + Mila (Quebec AI Institute)Verified email at stanford.edu
Karsten RothPhD Student (ELLIS, IMPRS-IS), Explainable Machine Learning Group, University of TuebingenVerified email at uni-tuebingen.de
John GuttagVerified email at mit.edu
Daryush D. Mehta, PhDDirector of Voice Science and Technology Laboratory, Center for Laryngeal Surgery and VoiceVerified email at alum.mit.edu
Jarrad H Van StanHarvard Medical School and Massachusetts General HospitalVerified email at mghihp.edu
Finale Doshi-VelezProfessor, HarvardVerified email at seas.harvard.edu
Harini SureshPhD Student, Massachusetts Institute of Technology (MIT)Verified email at mit.edu
Shalmali JoshiHarvard UniversityVerified email at seas.harvard.edu
Haoran ZhangPhD Student, Massachusetts Institute of TechnologyVerified email at mit.edu
Rajesh RanganathAssistant Professor, NYUVerified email at cs.princeton.edu
Andrew L. BeamAssistant Professor, Harvard UniversityVerified email at hms.harvard.edu
Mengling 'Mornin' FengNational University of SingaporeVerified email at nus.edu.sg
Matías ZañartuDepartment of Electronic Engineering, Universidad Técnica Federico Santa MaríaVerified email at usm.cl
Michael C. HughesAssistant Professor of Computer Science, Tufts UniversityVerified email at michaelchughes.com

Dr. Marzyeh Ghassemi

Assistant Professor, EECS.CSAIL/IMES, MIT

Verified email at mit.edu - Homepage

Healthy ML Clinical Inference Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
COVID-19 Image Data Collection: Prospective Predictions Are the Future JP Cohen, P Morrison, L Dao, K Roth, TQ Duong, M Ghassemi arXiv preprint arXiv:2006.11988, 2020	459	2020
Do no harm: a roadmap for responsible machine learning for health care J Wiens, S Saria, M Sendak, M Ghassemi, VX Liu, F Doshi-Velez, K Jung, ... Nature medicine 25 (9), 1337-1340, 2019	297	2019
Unfolding Physiological State: Mortality Modelling in Intensive Care Units M Ghassemi, T Naumann, F Doshi-Velez, N Brimmer, R Joshi, ... KDD 2014, 2014	244	2014
A multivariate timeseries modeling approach to severity of illness assessment and forecasting in icu with sparse, heterogeneous clinical data M Ghassemi, MAF Pimentel, T Naumann, T Brennan, DA Clifton, ... Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015	211	2015
A Review of Challenges and Opportunities in Machine Learning for Health M Ghassemi, T Naumann, P Schulam, AL Beam, IY Chen, R Ranganath arXiv preprint arXiv:1806.00388, 2018	145*	2018
Predicting covid-19 pneumonia severity on chest x-ray with deep learning JP Cohen, L Dao, K Roth, P Morrison, Y Bengio, AF Abbasi, B Shen, ... Cureus 12 (7), 2020	144	2020
Can AI Help Reduce Disparities in General Medical and Mental Health Care? IY Chen, P Szolovits, M Ghassemi AMA Journal of Ethics 21 (2), 167-179, 2019	137	2019
Continuous state-space models for optimal sepsis treatment: a deep reinforcement learning approach A Raghu, M Komorowski, LA Celi, P Szolovits, M Ghassemi Machine Learning for Healthcare Conference, 147-163, 2017	133	2017
Challenges to the reproducibility of machine learning models in health care AL Beam, AK Manrai, M Ghassemi Jama 323 (4), 305-306, 2020	122	2020
Predicting early psychiatric readmission with natural language processing of narrative discharge summaries A Rumshisky, M Ghassemi, T Naumann, P Szolovits, VM Castro, ... Translational psychiatry 6 (10), e921-e921, 2016	120	2016
Using ambulatory voice monitoring to investigate common voice disorders: Research update DD Mehta, JH Van Stan, M Zañartu, M Ghassemi, JV Guttag, ... Frontiers in bioengineering and biotechnology 3, 155, 2015	115	2015
State of the art review: the data revolution in critical care M Ghassemi, LA Celi, DJ Stone Critical Care 19 (1), 1-9, 2015	111	2015
State of the Art Review: The Data Revolution in Critical Care M Ghassemi, LA Celi, JD Stone Annual Update in Intensive Care and Emergency Medicine 2015, 573-586, 2015	111	2015
Clinically accurate chest x-ray report generation G Liu, TMH Hsu, M McDermott, W Boag, WH Weng, P Szolovits, ... Machine Learning for Healthcare Conference, 249-269, 2019	105	2019
Deep Reinforcement Learning for Sepsis Treatment A Raghu, M Komorowski, I Ahmed, L Celi, P Szolovits, M Ghassemi arXiv preprint arXiv:1711.09602, 2017	101	2017
Clinical Intervention Prediction and Understanding using Deep Networks H Suresh, N Hunt, A Johnson, LA Celi, P Szolovits, M Ghassemi arXiv preprint arXiv:1705.08498, 2017	83	2017
Clinical Intervention Prediction and Understanding with Deep Neural Networks H Suresh, N Hunt, A Johnson, LA Celi, P Szolovits, M Ghassemi Machine Learning for Healthcare Conference, 322-337, 2017	78	2017
Making big data useful for health care: a summary of the inaugural mit critical data conference O Badawi, T Brennan, LA Celi, M Feng, M Ghassemi, A Ippolito, ... JMIR medical informatics 2 (2), e3447, 2014	75	2014
Making big data useful for health care: a summary of the inaugural mit critical data conference O Badawi, T Brennan, LA Celi, M Feng, M Ghassemi, A Ippolito, ... JMIR medical informatics 2 (2), e3447, 2014	73	2014
CheXclusion: Fairness gaps in deep chest X-ray classifiers L Seyyed-Kalantari, G Liu, M McDermott, IY Chen, M Ghassemi BIOCOMPUTING 2021: Proceedings of the Pacific Symposium, 232-243, 2020	68	2020

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