Colorectal cancer (CRC) prevention depends on effective colonoscopy; yet variability in adenoma detection rates (ADRs) and missed lesions remain significant hurdles. Artificial intelligence-powered computer-aided detection (CADe) systems offer promising advancements in enhancing polyp detection. This review examines the role of CADe in improving ADR and reducing adenoma miss rates (AMRs) while addressing its broader clinical implications. CADe has demonstrated consistent improvements in ADRs and AMRs; largely by detecting diminutive polyps, but shows limited efficacy in identifying advanced adenomas or sessile serrated lesions. Challenges such as operator deskilling and the need for enhanced algorithms persist. Combining CADe with adjunctive techniques has shown potential for further optimizing performance. While CADe has standardized detection quality; its long-term impact on CRC incidence and mortality remains inconclusive. Future research should focus on refining CADe technology and assessing its effectiveness in reducing the global burden of CRC.
结直肠癌的预防依赖于有效的结肠镜检查，但腺瘤检出率的差异和漏诊病变仍是重要障碍。人工智能驱动的计算机辅助检测系统为提升息肉检出能力提供了前景广阔的技术进展。本文综述了计算机辅助检测在提高腺瘤检出率、降低腺瘤漏诊率方面的作用，并探讨其更广泛的临床意义。该系统主要通过检测微小息肉，在提升腺瘤检出率和降低漏诊率方面展现出持续改善效果，但在识别进展期腺瘤和无蒂锯齿状病变方面效果有限。操作者技能退化风险及算法优化需求等挑战依然存在。将计算机辅助检测与辅助技术结合使用，显示出进一步优化性能的潜力。尽管该系统已实现检测质量的标准化，但其对结直肠癌发病率和死亡率的长期影响尚未明确。未来研究应聚焦于完善计算机辅助检测技术，并评估其在降低全球结直肠癌疾病负担方面的实际效果。
肿瘤(癌症)患者之家