Longitudinal NSCLC Treatment Progression via Multimodal Generative Models
Longitudinal NSCLC Treatment Progression via Multimodal Generative Models explores Predict tumor evolution during radiotherapy by synthesizing plausible follow-up CT images conditioned on radiation dose and clinical variables, enabling in-silico treatment monitoring and adaptive radiotherapy research.. Commercial viability score: 7/10 in Medical AI.
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