
Digital Twins Solve Rare Disease Trial Dilemma
Using virtual clones to simulate disease progression could finally solve the recruitment bottleneck that stalls rare disease drug development.
Discover the newest research about AI innovations in Research.

Using virtual clones to simulate disease progression could finally solve the recruitment bottleneck that stalls rare disease drug development.

A new machine learning model uses basic blood markers to predict how kidney cancer patients respond to immunotherapy.

A massive funding injection promises to free doctors from keyboards, but the financial plumbing of the NHS could stall the rollout.

A new digital twin model shows that one-third of heart failure patients fail cardiac therapy because surgeons are aiming at the wrong target.

An ambitious clinical trial across Australasia is about to test whether machine learning can make split-second decisions to save critically ill patients.

By combining two different genomic signals, researchers proved that cheap, shallow DNA sequencing can catch ovarian cancer with high accuracy.

The acquisition of Aster by Elation Health signals a major shift from AI that merely listens to AI that actively operates.

A new deep learning model spots chronic kidney disease using routine heart ultrasounds, bypassing the need for immediate blood work.

A $55 million bet on rapid online training exposes the deep cracks in traditional medical education.

A new benchmark shows that expensive tabular foundation models offer almost no performance advantage over classic machine learning for predicting patient outcomes.