2022
DOI: 10.3390/s22051803
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Untangling Computer-Aided Diagnostic System for Screening Diabetic Retinopathy Based on Deep Learning Techniques

Abstract: Diabetic Retinopathy (DR) is a predominant cause of visual impairment and loss. Approximately 285 million worldwide population is affected with diabetes, and one-third of these patients have symptoms of DR. Specifically, it tends to affect the patients with 20 years or more with diabetes, but it can be reduced by early detection and proper treatment. Diagnosis of DR by using manual methods is a time-consuming and expensive task which involves trained ophthalmologists to observe and evaluate DR using digital fu… Show more

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Cited by 34 publications
(12 citation statements)
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“…[42] provides a robot-based engagement method for kindergarten students with autism to strengthen their narrative abilities. NAO was used to facilitate communication and gestures amongst patients who spoke Chinese [47][48][49]. According to the researchers' findings, children are better able than physicians to conduct constructive conversations with robots.…”
Section: Children With Asd May Be Diagnosed and Theirmentioning
confidence: 99%
“…[42] provides a robot-based engagement method for kindergarten students with autism to strengthen their narrative abilities. NAO was used to facilitate communication and gestures amongst patients who spoke Chinese [47][48][49]. According to the researchers' findings, children are better able than physicians to conduct constructive conversations with robots.…”
Section: Children With Asd May Be Diagnosed and Theirmentioning
confidence: 99%
“…30 different ultrasonic techniques have been reported. Multiple reports were made on 7 techniques [39][40][41][42].…”
Section: Related Workmentioning
confidence: 99%
“…Researchers can obtain data sets publicly. However, obtaining and gathering private data without official consent raises ethical concerns, especially when the study involves sensitive patient information [233]. However, research has demonstrated that human biases, such as racial and gender bias, can be reinforced by AI systems in multiple contexts [234,235,236].…”
Section: Ethical Issuesmentioning
confidence: 99%