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ASH 2025 | AI in myeloid neoplasm risk models: addressing the “black box” problem
Gianluca Asti, MSc, Humanitas Clinical and Research Center, IRCCS, Rozzano, Italy, discusses efforts to address the “black box” problem in artificial intelligence (AI) by integrating explainable frameworks into morphology-based risk models for myeloid neoplasms. He emphasizes the need for robust, multicenter data and standardized feature extraction before AI-driven insights can be incorporated into clinical risk scores. This interview took place at the 67th ASH Annual Meeting and Exposition, held in Orlando, FL.
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