Application and observation of artificial intelligence in clinical practice of fundus screening for diabetic retinopathy with non-mydriatic fundus photography: a retrospective observational study of T2DM patients in Tianjin, China.
Zhaohu HaoRong XuXiao HuangXinjun RenHuanming LiHailin ShaoPublished in: Therapeutic advances in chronic disease (2022)
Non-mydriasis fundus examination combined with AI has a medium-high consistency with ophthalmologists in DR diagnosis, conducive to early DR screening. Combining diagnosis and treatment modes with the Internet can promote the development of telemedicine, alleviate the shortage of ophthalmology resources, and promote the process of blindness prevention and treatment projects.
Keyphrases
- diabetic retinopathy
- artificial intelligence
- machine learning
- optical coherence tomography
- big data
- deep learning
- clinical practice
- end stage renal disease
- ejection fraction
- newly diagnosed
- prognostic factors
- editorial comment
- type diabetes
- quality improvement
- health information
- social media
- patient reported
- weight loss