Health informatics

A bottleneck in ensuring access to widespread molecular diagnostics, especially in low- and middle-income countries, has been the high cost and logistical complexities associated with rapid, point-of-care tests.

Weeks after President Donald Trump took office, multiple government webpages referencing gender and sexual orientation abruptly disappeared from the internet.

There are more than 100,000 people on organ transplant lists in the U.S., some of whom will wait years to receive one—and some may not survive the wait. Even with a good match, there is a chance that a person’s body will reject the organ. To shorten waiting periods and reduce the possibility of rejection, researchers in regenerative medicine are developing methods to use a patient’s own cells to fabricate personalized hearts, kidneys, livers, and other organs on demand.

Medical professionals have been using artificial intelligence (AI) to streamline diagnoses for decades, using what are called diagnostic decision support systems (DDSSs). Computer scientists at Massachusetts General Hospital (MGH) first developed MGH’s own DDSS called DXplain in 1984, which relies on thousands of disease profiles, clinical findings, and data points to generate and rank potential diagnoses for use by clinicians.

OpenAI has unveiled a large dataset to help test how well artificial intelligence (AI) models answer health care questions.

Dr. Google is often on call for worried patients, but it may not give the best advice.

The hottest trend on the horizon for artificial intelligence (AI) is agentic AI, according to Jason Moore, Ph.D., chair of the Department of Computational Biomedicine at Cedars-Sinai.

A powerful new software platform called the Playbook Workflow Builder is set to transform biomedical research by allowing scientists to conduct complex and customized data analyses without advanced programming skills.

New ILR School-led research offers a comprehensive overview of the role of health information technology (IT) in the financialization of the health care industry—the extent to which Silicon Valley and Wall Street investors have profited on health IT systems that have often failed to deliver promised gains.

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.