[Clinical value of medical imaging artificial intelligence in the diagnosis and treatment of peritoneal metastasis in gastrointestinal cancers].

Q3 Medicine
M J Fang, D Dong, J Tian
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引用次数: 0

Abstract

Peritoneal metastasis is a key factor in the poor prognosis of advanced gastrointestinal cancer patients. Traditional radiological diagnostic faces challenges such as insufficient sensitivity. Through technologies like radiomics and deep learning, artificial intelligence can deeply analyze the tumor heterogeneity and microenvironment features in medical images, revealing markers of peritoneal metastasis and constructing high-precision predictive models. These technologies have demonstrated advantages in tasks such as predicting peritoneal metastasis, assessing the risk of peritoneal recurrence, and identifying small metastatic foci during surgery. This paper summarizes the representative progress and application prospects of medical imaging artificial intelligence in the diagnosis and treatment of peritoneal metastasis, and discusses potential development directions such as multimodal data fusion and large model. The integration of medical imaging artificial intelligence with clinical practice is expected to advance personalized and precision medicine in the diagnosis and treatment of peritoneal metastasis in gastrointestinal cancers.

[医学影像人工智能在胃肠道肿瘤腹膜转移诊治中的临床价值]。
腹膜转移是导致晚期胃肠道肿瘤患者预后不良的关键因素。传统的放射诊断面临灵敏度不足等挑战。人工智能通过放射组学、深度学习等技术,深入分析医学图像中的肿瘤异质性和微环境特征,揭示腹膜转移标志物,构建高精度预测模型。这些技术在预测腹膜转移、评估腹膜复发风险和识别手术过程中的小转移灶等方面具有优势。综述了医学影像人工智能在腹膜转移诊治中的代表性进展及应用前景,并探讨了多模态数据融合、大模型等潜在发展方向。将医学影像人工智能与临床实践相结合,有望在胃肠道肿瘤腹膜转移的诊断和治疗中推进个性化和精准医疗。
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来源期刊
中华胃肠外科杂志
中华胃肠外科杂志 Medicine-Medicine (all)
CiteScore
1.00
自引率
0.00%
发文量
6776
期刊介绍:
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