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Guidelines on clinical research evaluation of artificial intelligence in ophthalmology (2023).
Yang, Wei-Hua; Shao, Yi; Xu, Yan-Wu.
Affiliation
  • Yang WH; Shenzhen Eye Institute, Shenzhen Eye Hospital, Shenzhen 518040, Guangdong Province, China.
  • Shao Y; The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China.
  • Xu YW; School of Future Technology, South China University of Technology, Guangzhou 510641, Guangdong Province, China.
Int J Ophthalmol ; 16(9): 1361-1372, 2023.
Article in En | MEDLINE | ID: mdl-37724285
With the upsurge of artificial intelligence (AI) technology in the medical field, its application in ophthalmology has become a cutting-edge research field. Notably, machine learning techniques have shown remarkable achievements in diagnosing, intervening, and predicting ophthalmic diseases. To meet the requirements of clinical research and fit the actual progress of clinical diagnosis and treatment of ophthalmic AI, the Ophthalmic Imaging and Intelligent Medicine Branch and the Intelligent Medicine Committee of Chinese Medicine Education Association organized experts to integrate recent evaluation reports of clinical AI research at home and abroad and formed a guideline on clinical research evaluation of AI in ophthalmology after several rounds of discussion and modification. The main content includes the background and method of developing this guideline, an introduction to international guidelines on the clinical research evaluation of AI, and the evaluation methods of clinical ophthalmic AI models. This guideline introduces general evaluation methods of clinical ophthalmic AI research, evaluation methods of clinical ophthalmic AI models, and commonly-used indices and formulae for clinical ophthalmic AI model evaluation in detail, and amply elaborates the evaluation methods of clinical ophthalmic AI trials. This guideline aims to provide guidance and norms for clinical researchers of ophthalmic AI, promote the development of regularization and standardization, and further improve the overall level of clinical ophthalmic AI research evaluations.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Guideline / Prognostic_studies / Qualitative_research Language: En Journal: Int J Ophthalmol Year: 2023 Document type: Article Affiliation country: China Country of publication: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Guideline / Prognostic_studies / Qualitative_research Language: En Journal: Int J Ophthalmol Year: 2023 Document type: Article Affiliation country: China Country of publication: China