A research team led by investigators from the NIH and Global Good has developed a computer algorithm that can analyze digital images of a woman’s cervix and accurately identify precancerous changes that require medical attention. This artificial intelligence approach, called automated visual evaluation, has the potential to revolutionize cervical cancer screening, particularly in low-resource settings.
Kevan Shokat, a professor of cellular and molecular pharmacology at UC San Francisco, has won the second annual Stephenson Global Prize for research in pancreatic cancer.
