Contrary to common understanding, sepsis is not a one-size-afflicts-all condition. It’s a set of many, and each can be placed into one of four key subcategories—i.e., phenotypes—such that, going forward, stricken patients could receive tailored treatments.

Researchers say such misnomers could have major policy implications, especially in an increasingly value-based landscape.

A natural language processing algorithm has achieved 90% precision in automatically spotting signs of social isolation in cancer patients by “reading” clinical notes in a hospital’s electronic health record.

As healthcare operators continually rely on medical devices in workflows, unsupported devices are likely to become more vulnerable to cyberattacks.

Academic and popular writings on the use of “embodied” AI in mental healthcare are piling up fast. But where’s the guidance for psychiatrists, psychotherapists and clinical social workers looking to use robots, avatars and chatbots with real patients?

Instead of Googling symptoms to when feeling an ailment and landing on an incorrect diagnosis, AI could soon provide accurate diagnosis without needing to go to a doctor’s office.

AI can speed up precise detection of one of the key signs of Alzheimer’s disease, according to researchers from University of California Davis and UC San Francisco, who published a study on their machine learning tool in Nature Communications.

Civica Rx, a not-for-profit drug company startup that aims to provide more affordable drugs, inked a new deal to distribute antibiotics with Xellia Pharmaceuticals, a specialty pharmaceutical company based in Copenhagen that develops, manufactures and commercializes anti-infective treatments.