摘要
Abstract
In recent years,artificial intelligence(AI)technology has shown tremendous application potential in the fields of medical imaging and pathology.As a major achievement of digital technology,digital pathology converts traditional slides into high-resolution digital images and applies AI for deep analysis,thereby optimizing the diagnostic workflow and improving efficiency.Renal cell carcinoma(RCC)is the most common malignant tumor of the kidney,and precise pathological diagnosis of RCC is crucial for the implementation of individualized targeted therapy.Currently,digital pathology is widely applied in the histopathological diagnosis and subtype classification of RCC and further extended to tumor grading,molecular profiling,and prognostic risk prediction.Deep learning-based image analysis enables accurate recognition,subtype classification,and prognosis prediction of RCC pathological images.Moreover,the integration of AI with multimodal data has significantly improved the diagnostic accuracy of RCC.However,practical applications of AI in RCC pathology still face multiple challenges,including insufficient data standardization,limited model interpretability,and lack of robust multi-center validation systems.Despite these obstacles,AI is expected to become a pivotal technological support for revolutionizing RCC clinical diagnosis and treatment models.关键词
人工智能/肾细胞癌/放射组学/数字病理学/深度学习Key words
artificial intelligence/renal cell carcinoma/radiomics/digital pathology/deep learning
