Harvard-MIT Health Sciences and Technology
Harvard-MIT Health Sciences and Technology

Can AI help predict which heart-failure patients will worsen within a year?

Researchers at MIT, Mass General Brigham, and Harvard Medical School developed a deep-learning model to forecast a patient’s heart failure prognosis up to a year in advance.

3 Questions: Using AI to accelerate the discovery and design of therapeutic drugs

Professor James Collins discusses how collaboration has been central to his research into combining computational predictions with new experimental platforms.

Five with MIT ties elected to National Academy of Medicine for 2025

Professors Facundo Batista and Dina Katabi, along with three additional MIT alumni, are honored for their outstanding professional achievement and commitment to service.

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.

Three MIT students selected as inaugural MIT-Pillar AI Collective Fellows

The graduate students will aim to commercialize innovations in AI, machine learning, and data science.

2023-24 Takeda Fellows: Advancing research at the intersection of AI and health

Thirteen new graduate student fellows will pursue exciting new paths of knowledge and discovery.

How to help high schoolers prepare for the rise of artificial intelligence

A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds.

MIT researchers combine deep learning and physics to fix motion-corrupted MRI scans

The challenge involves than just a blurry JPEG. Fixing motion artifacts in medical imaging requires a more sophisticated approach.

MIT scientists build a system that can generate AI models for biology research

BioAutoMATED, an open-source, automated machine-learning platform, aims to help democratize artificial intelligence for research labs.