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.
The NCI Human Tumor Atlas Network (HTAN) has published a cluster of papers intended to advance the framework of spatial omics, the science of profiling morphological and molecular features of human cancers in two and three dimensions.
