人工智能和大数据在泌尿瘤学:从放射学到现实世界的证据
Stamatios Katsimperis1, Lazaros Tzelves1, Ioannis Kyriazis1
1Second Department of Urology, National and Kapodistrian University of Athens, Sismanogleio Hospital, 15126 Athens, Greece.
Archivos espanoles de urologia
|March 3, 2026
概括
人工智能 (AI) 和大数据正在彻底改变泌尿瘤学,改善癌症诊断和治疗个性化. 对于这些AI工具的广泛临床采用,需要进一步验证.
科学领域:
- 泌尿外科瘤学 泌尿外科瘤学
- 人工智能的人工智能
- 大数据分析大数据分析
背景情况:
- 人工智能 (AI) 和大数据正在改变泌尿外科瘤学.
- 提高诊断精度,预后评估,以及针对前列腺,膀和癌的个性化治疗.
研究的目的:
- 审查人工智能和大数据在泌尿瘤学中的应用和影响.
- 评估人工智能模型在常见泌尿病恶性瘤中的诊断和预后能力.
主要方法:
- 在PubMed和MEDLINE系统搜索到2025年9月.
- 包括英语,同行评审的人类研究.
- 关键词:人工智能,深度学习,放射学,现实世界的证据,泌尿瘤学.
主要成果:
- 人工智能驱动的放射学和深度学习模型在使用各种成像方式 (MRI,CT,PET) 和组织病理学检测和表征泌尿系统恶性瘤方面表现出高准确度 (AUC 0.80-0.95).
- 高诊断性能用于病变检测,分期和风险分层.
- 精确的突变预测 (85%-95%) 在癌和高灵敏度/特异性 (>90%) 在囊泡镜图像分析.
结论:
- 人工智能和大数据正在将诊断成像,病理学和临床实践整合到泌尿瘤学中.
- 持续的整合承诺精确,公平和适应性癌症护理.
- 挑战包括有限的外部验证和通用性;未来的进展需要多中心标准化和联合学习.
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