Abstract technology background

Machine Learning and Artificial Intelligence

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

Philippe Burlina

Principal Scientist, Intelligent Systems Center, Johns Hopkins Applied Physics Laboratory

Brian Caffo

Professor, Bloomberg School of Public Health

Nilanjan Chatterjee

Bloomberg Distinguished Professor of Biostatistics and Oncology

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

Chien-Ming Huang

John C. Malone Assistant Professor of Computer Science

Ferdinand Hui

Co-Director, Radiology Artificial Intelligence Lab (RAIL)

Tin Yan Alvin Liu

Assistant Professor of Ophthalmology, Johns Hopkins School of Medicine

Michael Oberst

Assistant Research Professor of ComputerScience

Haris Sair

Co-Director, Radiology Artificial Intelligence Lab (RAIL)

Suchi Saria

John C. Malone Associate Professor of Computer Science

Mathias Unberath

Assistant Professor, Department of Computer Science

Swaroop Vedula

Associate Research Professor

Jeremy Waltson

Raymond and Anna Lublin Professor of Geriatric Medicine & Gerontology

Paul Yi

Adjunct Assistant Research Scientist, Malone Center for Engineering in Healthcare

Jithin Yohannan

Assistant Professor of Ophthalmology, Wilmer Eye Institute

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