Prediction of hypertension, hyperglycemia and dyslipidemia from retinal fundus photographs via deep learning: A cross-sectional study of chronic diseases in central China - Zhang, Li; Yuan, Mengya; An, Zhen; Zhao, Xiangmei; Wu, Hui; Li, Haibin; Wang, Ya; Sun, Beibei; Li, Huijun; Ding, Shibin; Zeng, Xiang; Chao, Ling; et al. (PloS one, 2020)
Keywords: Algorithms; Alzheimer's disease; Anthropometry; Artificial intelligence; Artificial neural networks; Biochemistry; Blood pressure; Blood tests; Body mass index; Cardiovascular diseases; Chronic diseases; Chronic illnesses; Classification; Complications; Complications and side effects; Computer aided medical diagnosis; Computer and Information Sciences; Cross-sectional studies; Datasets; Deep learning; Diabetes mellitus; Diabetic retinopathy; Diseases; Dyslipidemia; Dyslipidemias; Erythrocytes; Glycosylated hemoglobin; Health risks; Heart diseases; Hematocrit; Hemoglobin; Hemoglobins; Hyperglycemia; Hypertension; Image quality; Machine learning; Mathematical models; Medical examination; Medical imaging; Medical imaging equipment; Medical research; Medicine and Health Sciences; Metabolic disorders; Methods; Neural networks; Parameters; People and Places; Photography; Population; Public health; Retina; Retinal images; Risk analysis; Risk factors; Rural areas; China