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This research explores green AI for cancer prediction using interpretable machine learning while reducing carbon footprints. It defines the scope by integrating carbon-aware AI techniques with clinical data, emphasizing model interpretability. The methodology includes multi-objective optimization through E3-NAS, clinical validation, and comprehensive performance assessments. Expected contributions aim to reduce carbon emissions in healthcare AI, increase clinical trust, enhance usability, and...