Artificial intelligence (AI) has potential to transform healthcare. One area where AI is being employed is in lung cancer screenings using CT scans. Lung cancer is the number-one cancer killer in the United States, so methods to improve the screening process hold a lot of promise. However, AI technology in this area is not without its challenges.
In this episode of Critical Point, Milliman consultant Bruce Pyensen and Rush University Medical Center’s Jim Mulsine discuss the benefits and the challenges of using AI for lung cancer detection.
More people die from lung cancer globally than any other form of cancer. The disease is expected to kill over 154,000 people in the United States alone in 2018. Most recent reports about treating lung cancer have focused on innovative treatments around immunotherapy. But an alternative form of disease management exists that has been getting press attention: catching the disease early via CT scan.
Jim Mulshine, a thoracic medical oncologist by training who spent 25 years at the National Cancer Institute, and Bruce Pyenson, a consulting actuary at Milliman, sat down for a Q&A to discuss lung cancer and provide a medical and actuarial take around finding lung cancer early via CT scan.
In this Q&A, Mulshine, now at Rush University Medical Center, and Pyenson discuss the prognosis and progression of lung cancer, various treatments for the disease, including CT screening, and what future treatment could look like.