Researchers develop an AI model that can detect future lung cancer risk

The name Sybil may sound familiar to some as a popular given name for girls, with origins in Latin and meaning “prophetess”. However, this moniker carries deeper significance from antiquity, when sibyls were feminine oracles consulted to relay divine knowledge about the past, present, and future.

Now, researchers are breathing new life into the ancient name to brand an artificial intelligence tool looking to revolutionize the way we assess and treat lung cancer within healthcare. Sybil, developed by a team of researchers from MIT’s Abdul Latif Jameel Clinic for Machine Learning in Health, Mass General Cancer Center (MGCC), and Chang Gung Memorial Hospital (CGMH) enables clinicians to quickly and accurately determine a patient’s risk of developing or progressing lung cancer.

Sybil was largely motivated by the death of Gilbert Omenn, a pioneer in cancer research and a long-time supporter of the participating institutions. The team sought to develop a tool that allowed clinicians to make faster and more accurate assessments, in the hopes of increasing the efficiency and efficacy of lung cancer treatment and increasing patient outcomes.

Sybil is an example of how artificial intelligence, enabled by data science, is being used to revolutionize the field of medicine and healthcare. The technology that powers Sybil has the potential to help clinicians assess and treat myriad types of cancers, and its applications for the healthcare industry are virtually endless. And, as the team has paid homage to the ancient mythical figure who forecasted the future, Sybil may facilitate a future of improved healthcare outcomes and reduced mortality from cancer.






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