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Machine Learning and Artificial Intelligence

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Machine learning and AI-powered solutions have great potential to support busy health care providers. Malone researchers build better algorithms that help providers diagnose disease earlier, operate more precisely, streamline the patient experience, and more.

Researchers

Narges Ahmidi

Adjunct Assistant Research Scientist

Brian Caffo

Professor, Bloomberg School of Public Health

Nilanjan Chatterjee

Bloomberg Distinguished Professor of Biostatistics and Genetic Epidemiology

Yiqun Chen

Assistant Professor of Biostatistics and Computer Science

Martin Copenhaver

Assistant Professor of Emergency Medicine

Richard Day

Director, Precision Medicine Center of Excellence in Patient Safety and Quality, Armstrong Institute for Patient Safety

Mark Dredze

John C. Malone Professor of Computer Science

Nicholas Durr

Associate Professor of Biomedical Engineering

Gregory D. Hager

Mandell Bellmore Professor of Computer Science

Emily E. Haroz

Associate Professor of Mental and International Health

Chien-Ming Huang

John C. Malone Assistant Professor of Computer Science

Ananya Joshi

Assistant Professor of Psychiatry and Behavioral Sciences

Tin Yan “Alvin” Liu

Assistant Professor of Ophthalmology, Johns Hopkins School of Medicine

Michael Oberst

Assistant Research Professor of Computer Science

Vishal Patel

Associate Professor of Electrical and Computer Engineering

Haris Sair

Co-Director, Radiology Artificial Intelligence Lab (RAIL)

Suchi Saria

John C. Malone Associate Professor of Computer Science

Mathias Unberath

John C. Malone Associate Professor of Computer Science

Swaroop Vedula

Associate Research Professor

Jeremy Waltson

In memoriam

Srinivasan Yegnasubramanian

Professor of Oncology

Paul Yi

Adjunct Research Scientist

Jithin Yohannan

Assistant Professor of Ophthalmology, Wilmer Eye Institute

Zongwei Zhou

Assistant Research Scientist, Department of Computer Science

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Data Science for AI in Healthcare: An Online Course

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Noninvasive Localization of Epileptic Seizures

Epilepsy affects nearly 3.5 million people in the United States and is linked to a five-fold increase in mortality. While epilepsy is often controlled with medication, 20-40% of patients are medically refractory and continue to experience seizures in spite of drug therapies. The alternative for...

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Predicting Risk for Glaucoma Progression Based Using AI

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Radiology AI Lab (RAIL)

RAIL is an open structured artificial intelligence focused research collaboration based in the Hopkins Department of Radiology and Radiological Sciences. The group is comprised of physicians and scientists from Johns Hopkins Hospital, the Whiting School of Engineering, and the Applied Physics Laboratory,...

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