Artificial intelligence algorithms are everywhere in healthcare. They sort through patients’ data to predict who will develop medical conditions like heart disease or diabetes, they help doctors ...

Algorithms in clinical decision tools have been making it harder for certain racial and socioeconomic groups to receive the healthcare they deserve.

Others combine medical and demographic information to recommend a specific diagnostic test, or produce a risk score that helps determine whether a patient is a good candidate for a particular ...

A machine-learning algorithm can register brain scans and other 3D images more than 1000 times faster than traditional systems. (Courtesy: the researchers) Medical image registration involves ...

At the global HIMSS 1 Conference, Roche (RHHVF) showcases navify Algorithm Suite, a single platform offering clinicians access to medical algorithms generating insights to help improve care decisions.

AI is increasingly finding its way into healthcare decisions, from diagnostics to treatment decisions to robotic surgery. As I’ve written about in this newsletter many times, AI is sweeping the ...

hat’s in the box? The “black box,” that is. Increasingly, doctors are relying on sophisticated, and at times inscrutable, algorithms to make healthcare recommendations—a practice dubbed “black box ...

Most medical algorithms were developed using information from people treated in Massachusetts, California, or New York, according to a new study. Those three states dominate patient data — and 34 ...

Medical algorithms are used across the health-care spectrum to diagnose disease, offer prognoses, monitor patients’ health and assist with administrative tasks such as appointment scheduling. But the ...