Researchers at the University of Michigan Rogel Cancer Center have developed a computational platform that can predict new and specific metabolic targets in ovarian cancer, suggesting opportunities to develop personalized therapies for patients that are informed by the genetic makeup of their tumors. The study appeared in Nature Metabolism.

Members of the public are being asked to help remove biases based on race and other disadvantaged groups in artificial intelligence (AI) algorithms for healthcare.

Health researchers are calling for support to address how ‘minoritised’ groups, who are actively disadvantaged by social constructs, would not see future benefits from the use of AI in healthcare.

With conditions such as carpal tunnel syndrome and osteoarthritis on the rise, U.S. hand surgeons perform more than half a million procedures each year. Patients undergoing hand surgery commonly receive a regional anesthetic to block pain prior to the procedure, plus monitored anesthesia care (MAC) during the operation.

Social media users may trust artificial intelligence (AI) as much as human editors to flag hate speech and harmful content, according to researchers at Penn State.

The researchers said that when users think about positive attributes of machines, like their accuracy and objectivity, they show more faith in AI.

First, pause and take a deep breath.

When we breathe in, our lungs fill with oxygen, which is distributed to our red blood cells for transportation throughout our bodies. Our bodies need a lot of oxygen to function, and healthy people have at least 95% oxygen saturation all the time.

Researchers from the Epilepsy Neurogenetics Initiative (ENGIN) at Children's Hospital of Philadelphia (CHOP) found that across nearly 50,000 visits, patients continued to use telemedicine effectively even with the reopening of outpatient clinics a year after the onset of the COVID-19 pandemic. However, prominent barriers for socially vulnerable families and racial and ethnic minorities persist, suggesting more work is required to reach a wider population with telemedicine.

Harvard Medical School scientists and colleagues at Stanford University have developed an artificial intelligence (AI) diagnostic tool that can detect diseases on chest X-rays directly from natural-language descriptions contained in accompanying clinical reports.

The step is deemed a major advance in clinical AI design because most current AI models require laborious human annotation of vast reams of data before the labeled data are fed into the model to train it.