首页> 外文期刊>British Journal of Dermatology >Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma.
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Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma.

机译:皮肤镜检查和数字皮肤镜检查/人工智能对黑素瘤诊断的系统评价。

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摘要

BACKGROUND: Dermoscopy improves diagnostic accuracy of the unaided eye for melanoma, and digital dermoscopy with artificial intelligence or computer diagnosis has also been shown useful for the diagnosis of melanoma. At present there is no clear evidence regarding the diagnostic accuracy of dermoscopy compared with artificial intelligence. OBJECTIVES: To evaluate the diagnostic accuracy of dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis and to compare the diagnostic accuracy of the different dermoscopic algorithms with each other and with digital dermoscopy/artificial intelligence for the detection of melanoma. METHODS: A literature search on dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis was performed using several databases. Titles and abstracts of the retrieved articles were screened using a literature evaluation form. A quality assessment form was developed to assess the quality of the included studies. Heterogeneity among the studies was assessed. Pooled data were analysed using meta-analytical methods and comparisons between different algorithms were performed. RESULTS: Of 765 articles retrieved, 30 studies were eligible for meta-analysis. Pooled sensitivity for artificial intelligence was slightly higher than for dermoscopy (91% vs. 88%; P = 0.076). Pooled specificity for dermoscopy was significantly better than artificial intelligence (86% vs. 79%; P < 0.001). Pooled diagnostic odds ratio was 51.5 for dermoscopy and 57.8 for artificial intelligence, which were not significantly different (P = 0.783). There were no significance differences in diagnostic odds ratio among the different dermoscopic diagnostic algorithms. CONCLUSIONS: Dermoscopy and artificial intelligence performed equally well for diagnosis of melanocytic skin lesions. There was no significant difference in the diagnostic performance of various dermoscopy algorithms. The three-point checklist, the seven-point checklist and Menzies score had better diagnostic odds ratios than the others; however, these results need to be confirmed by a large-scale high-quality population-based study.
机译:背景:皮肤镜检查可提高肉眼对黑素瘤的诊断准确性,并且具有人工智能或计算机诊断功能的数字皮肤镜也已被证明可用于诊断黑素瘤。与人工智能相比,目前尚无关于皮肤镜诊断准确性的明确证据。目的:评估皮肤镜和数字皮肤镜/人工智能对黑色素瘤诊断的诊断准确性,并比较不同皮肤镜算法与数字皮肤镜/人工智能对黑色素瘤检测的诊断准确性。方法:使用多个数据库进行了皮肤镜检查和数字皮肤镜检查/人工智能对黑色素瘤诊断的文献检索。使用文献评估表筛选检索到的文章的标题和摘要。制定了质量评估表以评估纳入研究的质量。评估研究之间的异质性。使用荟萃分析方法分析汇总数据,并进行不同算法之间的比较。结果:在检索到的765篇文章中,有30项研究符合荟萃分析的条件。人工智能的综合敏感性略高于皮肤镜检查(91%比88%; P = 0.076)。皮肤镜检查的合并特异性显着优于人工智能(86%比79%; P <0.001)。皮肤镜检查的合并诊断优势比为51.5,人工智能的诊断优势比为57.8,差异无统计学意义(P = 0.783)。在不同的皮肤镜诊断算法之间,诊断几率没有显着差异。结论:皮肤镜检查和人工智能在诊断黑素细胞性皮肤病变方面表现同样出色。各种皮肤镜检查算法的诊断性能没有显着差异。三分检查表,七分检查表和孟席斯评分的诊断比值比值更高。但是,这些结果需要通过大规模高质量的基于人群的研究来证实。

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