Medicine
Medicine

When an antibiotic fails: MIT scientists are using AI to target “sleeper” bacteria

Most antibiotics target metabolically active bacteria, but with artificial intelligence, researchers can efficiently screen compounds that are lethal to dormant microbes.

Brain surgery training from an avatar

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

New model identifies drugs that shouldn’t be taken together

Using a machine-learning algorithm, researchers can predict interactions that could interfere with a drug’s effectiveness.

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.

What to do about AI in health?

Although artificial intelligence in health has shown great promise, pressure is mounting for regulators around the world to act, as AI tools demonstrate potentially harmful outcomes.

New hope for early pancreatic cancer intervention via AI-based risk prediction

MIT CSAIL researchers develop advanced machine-learning models that outperform current methods in detecting pancreatic ductal adenocarcinoma.

How an archeological approach can help leverage biased data in AI to improve medicine

Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.

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.

Supporting sustainability, digital health, and the future of work

The MIT and Accenture Convergence Initiative for Industry and Technology selects three new research projects to support.

How machine learning models can amplify inequities in medical diagnosis and treatment

MIT researchers investigate the causes of health-care disparities among underrepresented groups.