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Mohammad M. Ghassemi

Massachusetts Institute of Technology · US
Area of research
Emergency Medicine · Artificial Intelligence
Research interest
Research focused on Dosing and Electroencephalography, with related work in Coursework, Metric (unit), Photoplethysmogram. Notable publications include 'MIMIC-III, a freely accessible critical care database', 'Optimal medication dosing from suboptimal clinical examples: A deep reinforcement learning approach', and 'You Snooze, You Win: The PhysioNet/Computing in Cardiology Challenge 2018'.
h-index
citations
9,066
works
14
NIH funding
primary concept
email

Recent publications

AI-driven prediction of cardio-oncology biomarkers through protein corona analysis
Chemical Engineering Journal 2025cited by 15position: middledoi
The International Cardiac Arrest Research Consortium Electroencephalography Database
Critical Care Medicine 2023cited by 27position: middledoi
Real-time extended psychophysiological analysis of financial risk processing
PLoS ONE 2022cited by 37position: middledoi
Artifact Detection and Correction in EEG data: A Review
2021cited by 40position: lastdoi
Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning
IEEE Transactions on Biomedical Engineering 2021cited by 39position: middledoi
Quantitative EEG reactivity and machine learning for prognostication in hypoxic-ischemic brain injury
Clinical Neurophysiology 2019cited by 87position: middledoi
You Snooze, You Win: The PhysioNet/Computing in Cardiology Challenge 2018
Computing in cardiology 2018cited by 184position: firstdoi
Estimating the False Positive Rate of Absent Somatosensory Evoked Potentials in Cardiac Arrest Prognostication
Critical Care Medicine 2018cited by 59position: middledoi
A Deep Deterministic Policy Gradient Approach to Medication Dosing and Surveillance in the ICU
2018cited by 41position: middledoi
MIMIC-III, a freely accessible critical care database
Scientific Data 2016cited by 8,050position: middledoi
Optimal medication dosing from suboptimal clinical examples: A deep reinforcement learning approach
2016cited by 193position: middledoi
Monitoring and detecting atrial fibrillation using wearable technology
2016cited by 148position: middledoi
A “datathon” model to support cross-disciplinary collaboration
Science Translational Medicine 2016cited by 80position: middledoi
A data-driven approach to optimized medication dosing: a focus on heparin
Intensive Care Medicine 2014cited by 66position: firstdoi

Grants

No grants ingested yet.

Frequent collaborators

M. Brandon Westover · Rogers (United States)5 papers (2018–2023)Edilberto Amorim · University of California, San Francisco4 papers (2018–2023)Gari D. Clifford · Georgia Institute of Technology4 papers (2016–2023)Shamim Nemati · University of California San Diego3 papers (2016–2018)Leo Anthony Celi · Harvard University3 papers (2014–2016)Jong Woo Lee · Southwestern Medical Center3 papers (2019–2023)Tom Pollard · Massachusetts Institute of Technology2 papers (2016–2016)Nicolas Gaspard · Université Libre de Bruxelles2 papers (2021–2023)Benjamin Moody · Massachusetts Institute of Technology2 papers (2016–2018)Mengling Feng · National University of Singapore2 papers (2016–2016)Jeannette Hofmeijer · Amsterdam Neuroscience2 papers (2021–2023)Susan T. Herman · Barrow Neurological Institute2 papers (2021–2023)Sydney S. Cash · Harvard University2 papers (2018–2019)Wei‐Long Zheng · Shanghai Jiao Tong University2 papers (2021–2023)Jin Jing · East China University of Science and Technology2 papers (2019–2021)Li-wei H. Lehman · IBM (United States)2 papers (2016–2018)Michel J. A. M. van Putten · Medisch Spectrum Twente2 papers (2021–2023)Adithya Sivaraju · Yale Cancer Center2 papers (2021–2023)Andrew J. Cole · Medical University of South Carolina1 papers (2018–2018)Peter W. Kaplan · Johns Hopkins University1 papers (2018–2018)