Someone had to come right out and ask. Six researchers representing four medical specialties have done so, weighing the odds by reviewing a representative sample of the literature.

Industry researchers in medical AI have demonstrated a “causal reasoning” algorithm whose diagnostic accuracy would place it among the top 25% of primary care doctors in the U.K. 

Along with new or improved algorithmic applications for chest imaging, watch for word of an AI-powered breathalyzer and other diagnostic techno-weapons aimed at COVID. What they’ll all have in common is full-throated NIH support.

Researchers at New York University have demonstrated an AI-based way to send COVID patients from the ER to the most appropriate care setting according to their individualized risk.  

Machine learning can help post-childbirth mothers guard against problems with subsequent pregnancies, potentially saving their lives and those of their future babies.

Researchers have demonstrated the use of an AI tool that can accurately identify or rule out prostate cancer on digitized pathology slides from core needle biopsies.

The COVID crisis could close the gap between what healthcare AI can do in clinical research settings and how it can contribute to actual patient care.

The vast majority of patients with suspected melanoma—94%—would welcome the use of AI as an augmenter of their dermatologist’s diagnostic skills. And more than 40% would trust their diagnosis to a standalone AI system.  

Researchers have used AI-powered risk prediction to accurately screen the entire inpatient population of a community hospital for sepsis, enabling early treatment of the stricken.

The Mayo Clinic’s flagship campus in Minnesota is installing an AI-powered patient triage and prediction platform.