The vast majority of healthcare executives––89%––are experimenting with emerging technologies such as AI, according to Accenture’s Digital Health Technology Vision report.

Using a deep neural network equipped with all patient information relevant to diagnosing adult asthma, researchers in Japan have achieved 98% diagnostic accuracy.

Hoping to encourage interdisciplinary collaboration around Big Data over the next 50 to 100 years, Boston University is preparing to build a 17-story architectural marvel.

Facial recognition technology can be used to monitor sedated patients in intensive care units, alerting healthcare workers when a patient is at risk of accidentally removing a breathing tube or engaging in other risky behavior.

AI continues to wow healthcare watchers with sharp guidance on clinical decisionmaking, accurate aids to risk assessment and bankable workflow efficiencies. But healthcare was, is and always will be about “human-to-human relationships, trust and healing.”

Researchers in Texas and Taiwan have collaborated to develop a deep-learning tool that can precisely asses the risk of breast cancer—and with it the need for biopsy—in patients with lesions of questionable concern found in mammograms.

Diagnosing coronary artery disease, the most common type of heart disease in the U.S., can be improved by AI, according to a new, multicenter international study published in The Journal of Nuclear Medicine.

A healthcare AI startup striving to become the biggest provider of virtual medicine in India has gotten a boost in the form of investor dollars and friendly coverage in a prominent business journal.