AI algorithm enables tracking of vital white matter pathways Opening a new window on the brainstem, a new tool reliably and finely resolves distinct nerve bundles in live diffusion MRI scans, revealing signs of injury or disease. 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. Secrets of the sleep-deprived brain If you find it hard to focus after a wakeful night, it’s because your brain is busy trying to catch up on crucial housekeeping. MIT scientists, including an HST faculty member, investigate memorization risk in the age of clinical AI New research, including at IMES, demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data. Why it’s critical to move beyond overly aggregated machine-learning metrics New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy. Pagination First page « First Previous page Previous Page 1 Page 2 Current page 3 Page 4 Page 5 Page 6 Page 7 … Next page Next Last page Last »
AI algorithm enables tracking of vital white matter pathways Opening a new window on the brainstem, a new tool reliably and finely resolves distinct nerve bundles in live diffusion MRI scans, revealing signs of injury or disease.
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.
Secrets of the sleep-deprived brain If you find it hard to focus after a wakeful night, it’s because your brain is busy trying to catch up on crucial housekeeping.
MIT scientists, including an HST faculty member, investigate memorization risk in the age of clinical AI New research, including at IMES, demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
Why it’s critical to move beyond overly aggregated machine-learning metrics New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.
