The study, led by investigators from the Mass General Cancer Center, part of Boston-based Mass General Brigham, in collaboration with researchers at the Massachusetts Institute of Technology, created and tested Sybil, a machine learning tool designed to use a single low-dose chest scan to predict the risk of lung cancers occurring one to six years after a screening.
Sybil was able to accurately predict both short-term and long-term lung cancer risk, according to a Jan. 12 press release MIT shared with Becker’s. The study was published in the Journal of Clinical Oncology.
The researchers said this AI model aims to bring the research community one step closer to outgrowing legacy systems in the healthcare industry and help better treat current and future patients.
Becker’s 3rd Annual Fall Chief Pharmacy Officer Summit is the top tier event that the people leading the future of pharmacy convene. This 3-day event is built specifically for Chief Pharmacy Officers and senior pharmacy leaders. The sessions examine the workforce, financial and clinical priorities shaping pharmacy today. Becker’s is where candid discussions flourish and new ideas thrive. Becker's 3rd Annual Fall Chief Pharmacy Officer Summit
