Lessons From Oncology

Oncology has been an early adopter of machine learning in healthcare, and AI is now used to enhance cancer detection on imaging, facilitate more standardized pathologic review, generate more nuanced molecular signatures, process clinical data from electronic medical records, predict prognosis and response, and identify potential drug targets. In gastroenterology, AI can be used to improve the endoscopy suite, allowing gastroenterologists to better visualize abnormalities and recognize patterns. To bring AI-enabled products from an idea to the bedside, it is necessary to understand the current challenges faced by providers in a given specialty and address implementation obstacles to drive and expand adoption.