![]() The purpose of this article is to systematically review the original studies to answer the question: “What are the AI-based CAD applications in pediatric radiology, their diagnostic performances and methods for their performance evaluation?” 2. Hence, it is timely to conduct a systematic review about the diagnostic performance of AI-based CAD in pediatric radiology. ![]() ![]() Although the AI-based CAD is an important topic area in radiology, apparently, only two narrative reviews about various uses of AI in pediatric radiology (e.g., examination booking, image acquisition and post-processing, CAD, etc.) and AI-based CAD in pediatric chest imaging have been published to date. For example, the AI-based CAD systems for breast and prostate cancer detections seem not relevant to children. The aforementioned systematic review findings may not be applicable to the pediatric radiology. Pediatric radiology is a subset of radiology. In the future, more AI-based CAD studies in pediatric radiology with robust methodology should be conducted for convincing clinical centers to adopt CAD and realizing its benefits in a wider context. However, a range of methodological weaknesses (especially a lack of model external validation) are found in the included studies. This review shows that the AI-based CAD could be applied in pediatric brain, respiratory, musculoskeletal, urologic and cardiac imaging, and especially for pneumonia detection. Twenty-three articles that met the selection criteria were included. A literature search with the use of electronic databases was conducted on 11 January 2023. The purpose of this systematic review is to investigate the AI-based CAD applications in pediatric radiology, their diagnostic performances and methods for their performance evaluation. However, only two narrative reviews about general uses of AI in pediatric radiology and AI-based CAD in pediatric chest imaging have been published yet. Artificial intelligence (AI)-based computer-aided detection and diagnosis (CAD) is an important research area in radiology.
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