Deep learning could potentially assist healthcare providers with the evaluation of small renal masses detected on certain contrast-enhanced CT exams, according to a new study published in the American Journal of Roentgenology.

Machine learning (ML) technology has gained popularity in recent years, but its use in healthcare remains largely limited to proof-of-concept academic studies, according to a new study published in Artificial Intelligence in Medicine.

Researchers have developed a deep learning system capable of evaluating tissue samples and diagnosing prostate cancer at a level comparable with many pathologists.

Ambulatory care for cardiovascular conditions has improved in the U.S. over the past decade, according to data published in the Journal of the American College of Cardiology—but there’s still plenty of room to grow.

Anyone looking to learn more about blockchain should keep these limitations in mind at all times.

As costs continue to rise, healthcare organizations must become more efficient with collecting, says Anthony Cunningham, MBA, vice president of Patient Financial Services at Wake Forest Baptist Health. One approach, he explains, is deploying staff away from repetitive tasks and “toward high-value-add work.” That’s where artificial intelligence comes in.

The use of AI in healthcare is rapidly rising, but healthcare providers remain an absolutely essential part of patient care, according to a new analysis published in CMAJ.

Machine learning can play a key role in planning treatment for patients diagnosed with major depressive disorder (MDD), according to new research published in JAMA Network Open.