Artificial intelligence in diabetic retinopathy: A natural step to the future

Abstract

Use of artificial intelligence in medicine in an evolving technology which holds promise for mass screening and perhaps may even help in establishing an accurate diagnosis. The ability of complex computing is to perform pattern recognition by creating complex relationships based on input data and then comparing it with performance standards is a big step. Diabetic retinopathy is an ever-increasing problem. Early screening and timely treatment of the same can reduce the burden of sight threatening retinopathy. Any tool which can aid in quick screening of this disorder and minimize requirement of trained human resource for the same would probably be a boon for patients and ophthalmologists. In this review we discuss the current status of use of artificial intelligence in diabetic retinopathy and few other common retinal disorders.

Artificial Intelligence and Machine Learning Applied at the Point of Care

“…ML, embedded in medical devices or as a standalone software, has a potential to transform clinical practice and enhance patient outcomes while cutting down the healthcare costs (Hlatky et al, 2013;Padhy et al, 2019). This transformative potential will be realized when ML algorithms: (1) replace a physician in making a clinical diagnosis, (2) help resolve a clinical question in the primary rather than specialist care setting, (3) make it possible to effectively monitor a patient at home instead of at a hospital, and (4) make an accurate judgment about the type of treatment and dose of a drug.…”

Insights into the growing popularity of artificial intelligence in ophthalmology

“…Liability of the product, in case the algorithm commits an error in diagnosis and misses a diagnosis, is another aspect which lawmakers need to pay heed to while dealing with AI-based products or solutions. [ 36 ]…”

Diabetic Retinopathy Detection using Deep Learning Techniques

“…Balyen and Peto (2019) discuss the general influence of AI, ML and DL on the field of ophthalmology. Cheung et al (2019). suggest the potential of DL in the detection of DR and Diabetic Macular Edema (DME) from optical coherence tomography and digital fundus images.…”