Identification of ocular refraction based on deep learning algorithm as a novel retinoscopy method.

"Declarations Ethics approval and consent to participateThis study was approved by the Ethics Committee of Tianjin Eye Hospital and conducted in accordance with the tenets of the Declaration of Helsinki. The ethical committee waived the requirement for informed consent owing to the retrospective study design and the use of anonymized retinal fundus photographs. This study followed the Standards for Reporting of Diagnostic Accuracy Study-AI (STARD-AI) reporting guidelines. Consent for publicationNot applicable. Competing interestsThe authors declare that they have no competing interests. Competing interests The authors declare that they have no competing interests."

"Funding This study was supported by the National Natural Science Foundation of China (YW: 81873684),  the Tianjin Diversified Investment Fund for Applied Basic Research (21JCZDJC01190), and the Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-016A). The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication."

"This study was registered in the Chinese Clinical Trial Register (ChiCTR2100049885), approved by the Ethics Committee of Tianjin Eye Hospital, and conducted in accordance with the tenets of the Declaration of Helsinki. The ethical committee waived the requirement for informed consent owing to the retrospective study design and the use of anonymized RFPs. This study followed the Standards for Reporting of Diagnostic Accuracy Study-AI (STARD-AI) reporting guidelines []."