Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

Today, machine learning, artificial intelligence, and algorithmic advancements made by research scientists and engineers are driving more targeted medical therapies through the power of prediction.

New Mayo Clinic research finds that machine-learning algorithms can help health care staff distinguish the two conditions.

Machine learning (ML) algorithms that incorporate routinely collected patient-reported outcomes (PROs) alongside electronic health record (EHR) variables may improve prediction of short-term mortality ...

Machine learning, experts say, stands to empower doctors and benefit patients. But how will both respond to the idea of algorithms playing a bigger role in the medical system?

Using machine learning algorithms and human gut bacteria, scientists have developed a new low-cost screening method for detecting colorectal cancer.

As Big Data tools reshape health care, biased datasets and unaccountable algorithms threaten to further disempower patients.

Many of these machine-learning–aided tasks have been largely accepted and incorporated into the everyday practice of medicine.

Machine learning has had a significant impact in many areas of science and technology, including life science and medical research.

Becker has pursued interdisciplinary research for years, working closely with Dr. Su-In Lee to develop machine-learning algorithms for identifying effective cancer treatments.

In this view of the future of medicine, patient–provider interactions are informed and supported by massive amounts of data from interactions with similar patients. These data are collected and ...