Automatic Diagnosis of Diabetic Retinopathy Stage Focusing Exclusively on Retinal Hemorrhage

• Published in: Medicina Vol. 58; no. 11; p. 1681
• Main Authors: Tokuda, Yoshihiro, Tabuchi, Hitoshi, Nagasawa, Toshihiko, Tanabe, Mao, Deguchi, Hodaka, Yoshizumi, Yuki, Ohara, Zaigen, Takahashi, Hiroshi
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 20.11.2022; MDPI
• Subjects: Accuracy; Artificial Intelligence; Blood vessels; Cameras; Classification; Confidence intervals; deep convolutional neural network; deep learning; Development and progression; Diabetes; Diabetes Mellitus; Diabetic Retinopathy; Diagnosis; fundus ophthalmoscopy; fundus ophthalmoscopy; diabetic retinopathy; retinal hemorrhage; deep learning; deep convolutional neural network; Health aspects; Hemorrhage; Humans; Machine learning; Medicine (General); Methods; Prospective Studies; R5-920; Retina; Retinal Hemorrhage; Support vector machines; Japan

Background and Objectives: The present study evaluated the detection of diabetic retinopathy (DR) using an automated fundus camera focusing exclusively on retinal hemorrhage (RH) using a deep convolutional neural network, which is a machine-learning technology. Materials and Methods: This investigat...