Dr. Scott Gottlieb is a CNBC contributor and is a member of the boards of Pfizer, genetic testing startup Tempus, health-care tech company Aetion Inc. and biotech company Illumina. He is also a partner at the venture capital firm New Enterprise Associates. His editorial appeared on the CNBC website.
Researchers at Harvard presented a study demonstrating an achievement that would challenge any medical student. ChatGPT, a large language model, passed the U.S. Medical Licensing Exam, outperforming about 10 percent of medical students who fail the test annually.
The inevitable question isn’t so much if but when these artificial intelligence devices can step into the shoes of doctors. For some tasks, this medical future is sooner than we think.
To grasp the potential of these tools to revolutionize the practice of medicine, it pays to start with a taxonomy of the different technologies and how they’re being used in medical care.
The AI tools being applied to health care can generally be divided into two main categories. The first is machine learning, which uses algorithms to enable computers to learn patterns from data and make predictions. These algorithms can be trained on a variety of data types, including images.
The second category encompasses natural language processing, which is designed to understand and generate human language. These tools enable a computer to transform human language and unstructured text into machine-readable, organized data. They learn from a multitude of human trial-and-error decisions and emulate a person’s responses. Read more.
