التفاصيل البيبلوغرافية
| العنوان: |
A systematic review and meta-analysis of artificial intelligence versus clinicians for skin cancer diagnosis. |
| المؤلفون: |
Salinas, Maria Paz, Sepúlveda, Javiera, Hidalgo, Leonel, Peirano, Dominga, Morel, Macarena, Uribe, Pablo, Rotemberg, Veronica, Briones, Juan, Mery, Domingo, Navarrete-Dechent, Cristian |
| المصدر: |
NPJ Digital Medicine; 5/14/2024, Vol. 7 Issue 1, p1-23, 23p |
| مصطلحات موضوعية: |
MEDICAL information storage & retrieval systems, SKIN tumors, RECEIVER operating characteristic curves, DIAGNOSTIC imaging, RESEARCH funding, ARTIFICIAL intelligence, META-analysis, DESCRIPTIVE statistics, SYSTEMATIC reviews, MEDLINE, HOSPITAL medical staff, ODDS ratio, COMPUTER-aided diagnosis, MEDICAL databases, DERMOSCOPY, HISTOLOGICAL techniques, ONLINE information services, DATA analysis software, DERMATOLOGISTS, CONFIDENCE intervals, MACHINE learning, ALGORITHMS, SENSITIVITY & specificity (Statistics), EVALUATION |
| مستخلص: |
Scientific research of artificial intelligence (AI) in dermatology has increased exponentially. The objective of this study was to perform a systematic review and meta-analysis to evaluate the performance of AI algorithms for skin cancer classification in comparison to clinicians with different levels of expertise. Based on PRISMA guidelines, 3 electronic databases (PubMed, Embase, and Cochrane Library) were screened for relevant articles up to August 2022. The quality of the studies was assessed using QUADAS-2. A meta-analysis of sensitivity and specificity was performed for the accuracy of AI and clinicians. Fifty-three studies were included in the systematic review, and 19 met the inclusion criteria for the meta-analysis. Considering all studies and all subgroups of clinicians, we found a sensitivity (Sn) and specificity (Sp) of 87.0% and 77.1% for AI algorithms, respectively, and a Sn of 79.78% and Sp of 73.6% for all clinicians (overall); differences were statistically significant for both Sn and Sp. The difference between AI performance (Sn 92.5%, Sp 66.5%) vs. generalists (Sn 64.6%, Sp 72.8%), was greater, when compared with expert clinicians. Performance between AI algorithms (Sn 86.3%, Sp 78.4%) vs expert dermatologists (Sn 84.2%, Sp 74.4%) was clinically comparable. Limitations of AI algorithms in clinical practice should be considered, and future studies should focus on real-world settings, and towards AI-assistance. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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