Health Care
Health Care

Health Care

Artificial Intelligence Broad Institute Cancer Computer science and technology Diagnostics Disease Electrical Engineering & Computer Science (eecs) health Health Care IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Institutes of Health (NIH) Research School of Engineering

AI model identifies certain breast tumor stages likely to progress to invasive cancer

The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.

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MIT-Takeda Program wraps up with 16 publications, a patent, and nearly two dozen projects completed

The program focused on AI in health care, drawing on Takeda’s R&D experience in drug development and MIT’s deep expertise in AI.

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Symposium highlights scale of mental health crisis and novel methods of diagnosis and treatment

Co-hosted by the McGovern Institute, MIT Open Learning, and others, the symposium stressed emerging technologies in advancing understanding of mental health and neurological conditions.

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A data-driven approach to making better choices

In the new economics course 14.163 (Algorithms and Behavioral Science), students investigate the deployment of machine-learning tools and their potential to understand people, reduce bias, and improve society.

Artificial Intelligence Broad Institute Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) Health Care Imaging machine learning MIT Schwarzman College of Computing National Institutes of Health (NIH) Research School of Engineering

New AI method captures uncertainty in medical images

By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.

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Brain surgery training from an avatar

MIT.nano Immersion Lab works with AR/VR startup to create transcontinental medical instruction.

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Doctors have more difficulty diagnosing disease when looking at images of darker skin

Dermatologists and general practitioners are somewhat less accurate in diagnosing disease in darker skin, a new study finds. Used correctly, AI may be able to help.

Aeronautical and astronautical engineering Artificial Intelligence Aviation Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Digital technology Electrical Engineering & Computer Science (eecs) Ethics Health Care Institute for Medical Engineering and Science (IMES) Jameel Clinic machine learning MIT Schwarzman College of Computing School of Engineering Technology and policy Technology and society

Stratospheric safety standards: How aviation could steer regulation of AI in health

An interdisciplinary team of researchers thinks health AI could benefit from some of the aviation industry’s long history of hard-won lessons that have created one of the safest activities today.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical Engineering & Computer Science (eecs) Health Care Human-computer interaction IDSS Institute for Medical Engineering and Science (IMES) machine learning MIT Schwarzman College of Computing Research School of Engineering

Automated system teaches users when to collaborate with an AI assistant

MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.

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Meet the 2023-24 Accenture Fellows

The MIT and Accenture Convergence Initiative for Industry and Technology announces the 2023-24 graduate fellows.