MSK AI Models Bolster Patient Safety and Cancer Tracking

Memorial Sloan Kettering (MSK) researchers have developed a new artificial intelligence system, known as AI-ILS, to automate the review of medical incidents and "near-misses" ^[1][3]. The model utilizes the Human Factors Analysis and Classification System (HFACS) to identify safety threats and classify incident causes with 88% expert concordance ^[3]. Operating 29 times faster than traditional human review, the tool allows clinical teams to focus on designing safer workflows rather than administrative tasks ^[1][3]. In a parallel international study, MSK scientists deployed a machine-learning framework to analyze cancer survival disparities across 185 countries ^[1][2]. The AI-driven analysis identified three paramount drivers influencing national outcomes: economic strength, the availability of radiotherapy infrastructure, and the presence of universal health coverage ^[2]. By mapping these factors, the tool provides actionable roadmaps for policymakers to prioritize health system investments and close equity gaps ^[1][2].