人工智能在结直肠癌影像诊疗中的研究进展与展望OA

Precision diagnosis and treatment of colorectal cancer rely heavily on accurate medical imaging assessment.With the rapid advancement of artificial intelligence(AI),particularly radiomics and deep learning technologies,intelligent analysis tools based on CT and MRI have progressively permeated the entire clinical workflow of colorectal cancer diagno-sis and treatment.Focusing on core clinical challenges,this article systematically reviews the latest progress of AI in over-coming the limitations of traditional morphological imaging.It covers key areas such as preoperative precise staging as-sessment and molecular typing prediction,early prediction and evaluation of neoadjuvant treatment efficacy,and long-term risk assessment and clinical decision-making management.Furthermore,the article provides an in-depth analysis of current barriers hindering the clinical translation of AI models,including poor interpretability(the"black box"problem),insufficient multi-center generalizability,and the lack of data standardization.Future directions involving multimodal fu-sion and real-world research are also discussed.