Hanae Armitage

2 weeks ago | scopeblog.stanford.edu | Hanae Armitage

When a large language model first passed the United States Medical Licensing Exam in 2023, it was a big deal. But two years later, what was once a notable milestone in artificial intelligence progress is more of a bare minimum. "It's not enough for a large language model to simply answer medical test questions accurately," said Nigam H. Shah, MBBS, PhD, chief data scientist at Stanford Health Care.

1 month ago | medicalxpress.com | Hanae Armitage

Even cells experience peer pressure. Scientists have long studied the ins and outs of cancer cells to learn more about the disease, but they're increasingly finding that noncancerous cells near the cancer cells exert a powerful influence over a tumor's trajectory. "Not all cells in a tumor are cancer cells—they're not even always the most dominant cell type," said Sylvia Plevritis, Ph.D., chair of Stanford Medicine's department of biomedical data science.

1 month ago | scopeblog.stanford.edu | Hanae Armitage

Here's a question for anyone hoping to red light their way to a youthful complexion: Did you know that in dermatology red light treatment is used mostly for hair growth? It begs a more serious question for those of us already using red light in our skincare routine: Are we hoping to smooth out those wrinkles just to end up looking like Wolverine?

2 months ago | medicalxpress.com | Hanae Armitage

Artificial intelligence-powered chatbots are getting pretty good at diagnosing some diseases, but how do chatbots do when the questions are less black-and-white? For example, how long before surgery should a patient stop taking prescribed blood thinners? Should a patient's treatment protocol change if they've had adverse reactions to similar drugs in the past? These sorts of questions don't have a textbook right or wrong answer—it's up to physicians to use their judgment. Jonathan H.

Jan 10, 2025 | medicalxpress.com | Hanae Armitage

Stanford Medicine physicians have a new artificial intelligence tool to assist them when they message patients about test results. The technology drafts an interpretation of clinical test and lab results and explains them in a message using plain language, which a physician then reviews and approves.