Research

An AI algorithm created by Google can predict lung cancer with high accuracy and improve the survival chances of those with the cancer through earlier diagnosis, according to a recent study. The findings were published in Nature Medicine on May 20.

A Colorado teenager has won $75,000 for his machine learning and computer vision project that helps orthopedic surgeons improve the accuracy of screw placement during spinal surgery.

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?

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.

AI can predict death or heart attack better than humans, according to a new study presented at the International Conference on Nuclear Cardiology and Cardiac CT (ICNC) in Lisbon.

Combing through insurance claims and other health data on more than 72 million U.S. residents, a machine learning algorithm was able to quite accurately identify more than 222,000 individuals who have very early stage Alzheimer’s disease.

As medical devices are increasingly being touched by new AI innovations, the FDA will soon have to grapple with reality of regulating “living things” in a new way, according to a report from Roll Call.

The global excitement around healthcare’s embrace of AI and other developing technologies is not misplaced, but it needs to be tempered by an ongoing watchfulness for misuse.

Over the next 50 to 100 years, quantum computing will increasingly automate all manner of healthcare processes while biomaterials and genetic engineering drive regenerative medicine into everyday care.

There’s a lot of buzz about the applications of AI in the healthcare sector, but the innovations are still in infancy, leaving the potential use––and dangers––of AI in clinical settings unknown.

Drug development is on the cusp of becoming considerably faster, smarter and all-around better.

Options are increasing for healthcare consumers looking to check their symptoms with an AI digital platform for self-diagnosis. However, research into the use, accuracy and regulation of these technologies is woefully scant.