Health sciences and technology
Health sciences and technology

Health sciences and technology

Algorithms Artificial Intelligence Biology Cells Collaboration Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Disease Electrical engineering and computer science (EECS) Health sciences and technology machine learning MIT Schwarzman College of Computing Proteins Research School of Engineering School of Science Whitehead Institute

AI model deciphers the code in proteins that tells them where to go

Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.

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Can deep learning transform heart failure prevention?

A deep neural network called CHAIS may soon replace invasive procedures like catheterization as the new gold standard for monitoring heart health.

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Study reveals AI chatbots can detect race, but racial bias reduces response empathy

Researchers at MIT, NYU, and UCLA develop an approach to help evaluate whether large language models like GPT-4 are equitable enough to be clinically viable for mental health support.

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AI in health should be regulated, but don’t forget about the algorithms, researchers say

In a recent commentary, a team from MIT, Equality AI, and Boston University highlights the gaps in regulation for AI models and non-AI algorithms in health care.

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Improving health, one machine learning system at a time

Marzyeh Ghassemi works to ensure health-care models are trained to be robust and fair.

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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.

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From steel engineering to ovarian tumor research

Ashutosh Kumar, a materials science and engineering PhD student and MathWorks Fellow, applies his eclectic skills to studying the relationship between bacteria and cancer.

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Exploring frontiers of mechanical engineering

MIT Department of Mechanical Engineering grad students are undertaking a broad range of innovative research projects.