Worldwide, 240 million people have diabetes with 50% unaware of their condition. An estimated 2.5 million have diabetic retinopathy (DR), which is the leading cause of adult blindness. Fundus photography reading centers are overwhelmed by the growing number of DR cases to review. This study describes an automated artificial intelligence (AI) system that screens for DR. Subjects were recruited from the patient population at a medical university diabetes clinic. Dilated eyes (359 non- DR & 18 DR) and undilated eyes (130 non-DR & 11 DR) were used. Non-DR included normal and diabetic subjects with normal retinas or non-visually threatening (VT) disease. DR included only cases of VT disease. Cases in which retinal imaging was impossible (e.g., s...
International audienceINTRODUCTION:Since 2010, the High Authority for health (HAS) recommends the us...
Diabetic retinopathy is a common ocular complication of diabetes. It is the most frequent cause of b...
OBJECTIVE — To evaluate the performance of a system for automated detection of diabetic retinopathy ...
Worldwide, 240 million people have diabetes with 50% unaware of their condition. An estimated 2.5 mi...
Diabetes is a chronic disease affecting over 2% of the population in the UK [1]. Long-term complicat...
Aim: Diabetic retinopathy (DR) represents the main cause of vision loss among working age people. A ...
PURPOSE. To evaluate the performance of an automated fundus photographic image-analysis algorithm in...
Diabetic retinopathy (DR) is a leading cause of blindness among working-age adults. Early diagnosis ...
BACKGROUND: The automated screening of patients at risk of developing diabetic retinopathy represent...
Background: This study evaluated the operating characteristics of a reading software (Retinalyze® Sy...
Abstract Artificial Intelligence (AI) has long promised to increase healthcare affordability, qualit...
Artificial Intelligence has showcased clear capabilities to automatically grade diabetic retinopathy...
Automated identification of diabetic retinopathy (DR), the primary cause of blindness and visual los...
The aim of the study was to validate the performance of the Optomed Aurora® handheld fundus camera i...
Diabetic retinopathy (DR), one of the most devastating manifestations of diabetes, is a leading caus...
International audienceINTRODUCTION:Since 2010, the High Authority for health (HAS) recommends the us...
Diabetic retinopathy is a common ocular complication of diabetes. It is the most frequent cause of b...
OBJECTIVE — To evaluate the performance of a system for automated detection of diabetic retinopathy ...
Worldwide, 240 million people have diabetes with 50% unaware of their condition. An estimated 2.5 mi...
Diabetes is a chronic disease affecting over 2% of the population in the UK [1]. Long-term complicat...
Aim: Diabetic retinopathy (DR) represents the main cause of vision loss among working age people. A ...
PURPOSE. To evaluate the performance of an automated fundus photographic image-analysis algorithm in...
Diabetic retinopathy (DR) is a leading cause of blindness among working-age adults. Early diagnosis ...
BACKGROUND: The automated screening of patients at risk of developing diabetic retinopathy represent...
Background: This study evaluated the operating characteristics of a reading software (Retinalyze® Sy...
Abstract Artificial Intelligence (AI) has long promised to increase healthcare affordability, qualit...
Artificial Intelligence has showcased clear capabilities to automatically grade diabetic retinopathy...
Automated identification of diabetic retinopathy (DR), the primary cause of blindness and visual los...
The aim of the study was to validate the performance of the Optomed Aurora® handheld fundus camera i...
Diabetic retinopathy (DR), one of the most devastating manifestations of diabetes, is a leading caus...
International audienceINTRODUCTION:Since 2010, the High Authority for health (HAS) recommends the us...
Diabetic retinopathy is a common ocular complication of diabetes. It is the most frequent cause of b...
OBJECTIVE — To evaluate the performance of a system for automated detection of diabetic retinopathy ...