"These findings might imply that not all AFib is worth screening for, and not all screen-detected AFib merits anticoagulation," researchers wrote. 

Researchers tracked data from more than 3,600 patients who underwent either carotid endarterectomy or carotid artery stenting.

AI has shown strong potential for predicting which recently hospitalized patients will develop pressure injuries (PIs), also known as pressure ulcers or bedsores, if they aren’t treated early with preventive medicine.

After training deep neural networks on around 4,000 slide images from around 40 biopsied kidney patients, UCLA engineers have virtually re-stained tissue images for speedier high-accuracy diagnostics than a human histotechnologist could support.  

Researchers have achieved accuracies of 99.4% and 94.3% in two algorithmic methods for monitoring, diagnosing or ruling out Parkinson’s disease going only by individuals’ spoken words.

When drones and ambulances were both sent to the scene of a suspected cardiac arrest, the drone arrived first 64% of the time. 

Screening for sepsis in children and babies has grown quickly over the past several years. As methods and approaches multiply, machine learning continues looking like an eventual first-line diagnostic option. 

Researchers have used machine learning to accurately predict when a patient with chronic kidney disease will need dialysis. The technique may facilitate personalized care and optimized treatment planning.