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) ...

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?

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.

Should we let it? Machine learning is starting to take over analyzing medical images. But AI tools also raise worrying questions because they solve problems in ways that humans can’t always follow.

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

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 ...

Control theory is commonly used in the engineering of dynamic systems, but much less so by doctors. Associate Professor of Applied Mathematics Marcella Gomez’s research focuses on bridging that gap, ...

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

But, in general, those algorithms can be understood; this is not the case for algorithms based on machine learning where even the programmers do not know how the program is making decisions. The ...

So, Krakow and her team assembled the medical data of 350 relapse patients, 1,000 pages per, and put it toward building a machine-learning algorithm that could predict the best treatment sequence ...