A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms—addressing a ...

Katie Palmer covers telehealth, clinical artificial intelligence, and the health data economy — with an emphasis on the impacts of digital health care for patients, providers, and businesses. You can ...

The healthcare sector is increasingly reliant on digital technologies, demonstrating a strong commitment to using advanced tools for better patient care and more efficient data management. However, ...

HCA Healthcare inked a multi-year collaboration with Google Cloud focused on building a health data analytics platform to support the Nashville, Tenn.-based system’s clinical and operational workflows ...

This is Part 1 of Embedded Bias, a series revealing how race-based clinical algorithms pervade medicine and why it's so difficult to change them. Pediatrician Alexandra Epee-Bounya had had enough. In ...

Preparing cancer patients for difficult decisions is an oncologist’s job. They don’t always remember to do it, however. At the University of Pennsylvania Health System, doctors are nudged to talk ...

AI is riddled by bias, especially in healthcare. Just one well-known example is a study from 2019 that revealed racial bias in a clinical algorithm used by hospitals showing that Black patients had to ...

For years, it was harder for Black patients to secure a coveted spot on the national kidney transplant waitlist because a clinical algorithm was making Black patients appear healthier than they were.

While President Trump demands a single national framework on AI policy, states are going their own way with hundreds of proposals aimed at setting guardrails for how the technology is used in health ...