Anyone waiting for the results of a medical test knows the anxious question: "Will my life change completely when I know?" And the relief if you test negative. Today, artificial intelligence (AI) is increasingly deployed to predict life-threatening diseases. But there remains a big challenge in getting the machine learning (ML) algorithms to be precise enough--specifically, in getting the algorithms to correctly diagnose if someone is sick. Machine learning (ML) is the branch of AI where algorithms learn from datasets and get smarter in the process.

The Stanford Center for Health Education has launched an online program on Artificial Intelligence in Healthcare. Designed for technology professionals, computer scientists, and healthcare providers, the program aims to advance the delivery of patient care and improve global health outcomes through artificial intelligence and machine learning. The online program will be taught by faculty from Stanford Medicine. The program's goal is to foster a common understanding of the potential for AI to safely and ethically improve patient care. "Effective use of AI in healthcare requires knowing more than just the algorithms and how they work," says Nigam Shah, associate professor of medicine and biomedical data science, the faculty director of the new program.