Issues related to artificial intelligence research in ophthalmology
10.3760/cma.j.cn511434-20220210-00077
- VernacularTitle:眼科人工智能研究的相关问题
- Author:
Youxin CHEN
1
;
Shi FENG
;
Qing ZHAO
Author Information
1. 中国医学科学院 北京协和医学院 北京协和医院眼科, 北京 100730
- Keywords:
Artificial intelligence;
Diagnostic techniques, ophthalmological;
Image interpretation, computer-assisted;
Editorial
- From:
Chinese Journal of Ocular Fundus Diseases
2022;38(2):89-92
- CountryChina
- Language:Chinese
-
Abstract:
At present, artificial intelligence (AI) has been widely used in the diagnosis and treatment of various ophthalmological diseases, but there are still many problems. Due to the lack of standardized test sets, gold standards, and recognized evaluation systems for the accuracy of AI products, it is difficult to compare the results of multiple studies. When it comes to the field of image generation, we hardly have an efficient approach to evaluating research results. In clinical practice, ophthalmological AI research is often out of touch with actual clinical needs. The requirements for the quality and quantity of clinical data put more burden on AI research, limiting the transformation of AI studies. The prediction of systemic diseases based on fundus images is making progressive advancement. However, the lack of interpretability of the research lower the acceptance. Ophthalmology AI research also suffer from ethical controversy due to unconstructed regulations and regulatory mechanisms, concerns on patients' privacy and data security, and the risk of aggravating the unfairness of medical resources.
