The third feature in a series on AI in medicine highlights its role in developing early detection methods for ovarian cancer, which is rare, underfunded, and often diagnosed late. Dr. Daniel Heller at Memorial Sloan Kettering Cancer Center is using AI and nanotube technology to identify cancer-related molecules in blood samples.
Nanotubes, which emit fluorescent light, detect subtle molecular patterns in blood, too complex for human analysis. AI algorithms interpret these patterns, distinguishing ovarian cancer from other diseases with better accuracy than current biomarkers.
Challenges include limited data due to ovarian cancer’s rarity and minimal data sharing among hospitals. Despite this, early AI trials have shown promising results. With further refinement and larger datasets, Dr. Heller envisions using the technology to assist in diagnosing various gynecological conditions within 3–5 years.