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Towards an Explainable AI Platform to Study Interruptions in Cancer Radiation Therapy
Authors
Arash Shaban-Nejad, Nariman Ammar, Fekede Kumsa, Soheil Hashtarkhani, Brianna White, Lokesh K. Chinthala, Chase A. Owens, Neil Hayes, David L. Schwartz
Radiation therapy interruptions drive cancer treatment failures; they represent an untapped opportunity for improving outcomes and narrowing treatment disparities. This research reports on the early development of the X-CART platform, which uses explainable AI to model cancer treatment outcome metrics based on high-dimensional associations with our local social determinants of health dataset to identify and explain causal pathways linking social disadvantage with increased radiation therapy interruptions.
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