News-Medical.Net November 14, 2025
Medical imaging foundation models are ushering in a new era for precision oncology. By integrating massive multimodal datasets and advanced AI algorithms, these models achieve unprecedented accuracy in early cancer screening, treatment planning, and prognosis prediction. Leveraging innovations such as self-supervised learning, transformer architectures, and contrastive learning, they enable deep integration of radiology, pathology, and genomics data. This shift from “single-task diagnosis” to “multi-dimensional intelligent analysis” represents a paradigm innovation, redefining how tumors are detected and managed, and paving the way for data-driven, personalized oncology care.
Precision oncology demands accurate, individualized treatment strategies—yet clinical decision-making remains challenged by tumor heterogeneity, patient diversity, and limited data integration. Traditional AI models, trained for single diseases or tasks, struggle to generalize across cancer...
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