Sotabase

Career

· Associate Professor, Massachusetts Institute of Technology2021–
· Assistant Professor, University of Toronto2018–2021
· PhD Student, MIT Computer Science and Artificial Intelligence Laboratory2011–2017
· Visiting Researcher, Alphabet (Verily)
· BS in Computer Science and Electrical Engineering, New Mexico State University
· MSc in Biomedical Engineering, Oxford University

Publications (367)

The false hope of current approaches to explainable artificial intelligence in health care.
The Lancet Digital Health · 2021
950
cited
COVID-19 Image Data Collection: Prospective Predictions Are the Future
The Journal of Machine Learning for Biomedical Imaging · 2020
819
cited
Do no harm: a roadmap for responsible machine learning for health care
Nature Medicine · 2019
748
cited
Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations
Nature Medicine · 2021
645
cited
Ethical Machine Learning in Health Care
Annual Review of Biomedical Data Science · 2020
485
cited
AI recognition of patient race in medical imaging: a modelling study
The Lancet Digital Health · 2021
424
cited
CheXclusion: Fairness gaps in deep chest X-ray classifiers
Pacific Symposium on Biocomputing · 2020
349
cited
Do as AI say: susceptibility in deployment of clinical decision-aids
npj Digital Medicine · 2021
348
cited
Can AI Help Reduce Disparities in General Medical and Mental Health Care?
AMA journal of ethics · 2019
336
cited
A Review of Challenges and Opportunities in Machine Learning for Health.
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018
331
cited
Clinically Accurate Chest X-Ray Report Generation
Machine Learning in Health Care · 2019
322
cited
Challenges to the Reproducibility of Machine Learning Models in Health Care.
Journal of the American Medical Association (JAMA) · 2020
300
cited
MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III
ACM Conference on Health, Inference, and Learning · 2019
251
cited
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
Neural Information Processing Systems · 2022
247
cited
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare
British medical journal · 2023
245
cited
Reproducibility in machine learning for health research: Still a ways to go
Science Translational Medicine · 2021
234
cited
Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning
Cureus · 2020
231
cited
Unfolding physiological state: mortality modelling in intensive care units
Knowledge Discovery and Data Mining · 2014
230
cited
A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data
AAAI Conference on Artificial Intelligence · 2015
229
cited
The role of machine learning in clinical research: transforming the future of evidence generation
Trials · 2021
214
cited
Sotabase