Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms - Tsao, Hsin-Yi; Chan, Pei-Ying; Su, Emily Chia-Yu (BMC bioinformatics, 2018)
Keywords: Adult; Aged; Aged, 80 and over; Algorithms; Analysis; Artificial intelligence; Artificial neural networks; Bioinformatics; Biomedical and Life Sciences; Blood pressure; Clinical decision support; Clinical medicine; Computational biology; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Data mining; Datasets; Decision Support Systems, Clinical; Decision trees; Diabetes; Diabetes mellitus (non-insulin dependent); Diabetes Mellitus, Type 2 - complications; Diabetic retinopathy; Diabetic Retinopathy - diagnosis; Diabetic Retinopathy - etiology; Diagnosis; Edema; Female; Hemorrhage; Humans; Insulin; Learning algorithms; Life Sciences; Machine Learning; Male; Methods; Microarrays; Middle Aged; Neural networks; Neural Networks (Computer); Patients; Performance prediction; Prediction models; Retina; Retinopathy; Risk analysis; Risk Factors; ROC Curve; Studies; Support systems; Support vector machines; Test procedures; Diabetic retinopathy; Clinical decision support; Risk factors; Machine learning