Healthcare technology stories

Aug 7, 2026

AI Tool Successfully Detects Hard-to-Identify Heart Dysfunction from Standard ECGs

Researchers at Wake Forest University School of Medicine have developed an artificial intelligence model that can identify left ventricular dysfunction and heart failure with preserved ejection fraction from standard ECG readings, including conditions often missed in routine care.

Aug 7, 2026·2 sources

Jul 22, 2026

FDA Grants Marketing Authorization for Johnson & Johnson's OTTAVA Robotic Surgery System

The U.S. Food and Drug Administration has granted marketing authorization for Johnson & Johnson's OTTAVA robotic surgical system, enabling the healthcare conglomerate to enter the soft-tissue robotic surgery market for the first time.

Jul 22, 2026·5 sources

Top claims

▪In adults, the 12-lead AI model achieved areas under the curve of 0.90 for reduced ejection fraction, 0.81 for midrange ejection fraction, and 0.80 for heart failure with preserved ejection fraction.
▪Heart failure affects more than 6 million Americans and stands as a leading cause of hospitalization and death.
▪Heart failure with preserved ejection fraction is particularly challenging to detect in its early stages and is frequently overlooked during routine clinical evaluations.

Subtopics

Cardiovascular disease prevention AI data analysis AI research & benchmarks

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AI Tool Successfully Detects Hard-to-Identify Heart Dysfunction from Standard ECGs

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