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.

AI has “remarkable potential” to improve diagnostic accuracy, care efficiency and workflow optimization in the surgical subspecialty of burn care.

When the veteran cardiologist was first found guilty back in 2016, a U.S. attorney called the decision a “milestone in an investigation spanning several years.” 

More than 26,000 healthcare workers were surveyed in both 2015 and 2017, answering questions about exhaustion, burnout, job satisfaction and more.