diabetic retinopathy

The Role of AI in Medicine


Artificial intelligence (AI) is the enabling of machines to "think" like humans. The ability of AI to make data-driven decisions (pattern recognition) and to identify shared characteristics among data points are especially relevant to medicine (data mining). Spurred on by the explosive expansion of the Internet of Things (IoT) and the decreasing cost of cloud storage and computing, the AI health-care market is likely to exceed $34 billion by 2025, according to a report by Tractica. In this article, we will explore the ever-expanding application of AI in medical diagnosis, drug and device development, and operational improvement. IBM's Watson was the first AI platform to enter the field of medical research.

Jennifer Lim, MD: The Impact of Artificial Intelligence in DR Screening


EyeArt is an artificial intelligence system that has been developed and tested to help bridge the gap in screening for diabetic retinopathy. As the numbers of people with diabetes continue to grow, there aren't enough ophthalmologists and other health care providers to adequately screen for diabetic eye disease. Chair, Professor of Ophthalmology, and Director of Retina Service at the University of Illinois at Chicago presented the results of a clinical trial of the EyeArt system at the 2019 Association for Research in Vision and Ophthalmology (ARVO) Imaging in the Eye Conference in Vancouver, BC. Lim told MD Magazine that the EyeArt system has a "great ability to be useful to detect referable DR [diabetic retinopathy] from non-referable DR and what that really means in the practical sense is that the EyeArt system and this artificial intelligence system is useful in order to help triage patients and screen for diabetic retinopathy." She added that her hope that EyeArt will contribute to reducing blindness in this population in the future.

As Artificial Intelligence Moves Into Medicine, The Human Touch Could Be A Casualty

NPR Technology

When Kim Hilliard shows up at the clinic at the New Orleans University Medical Center, she's not there simply for an eye exam. The human touches she gets along the way help her navigate her complicated medical conditions. In addition to diabetes, the 56-year-old has high blood pressure. She has also had back surgery and has undergone bariatric surgery to help her control her weight. Hilliard is also at risk of blindness, which can result from a condition called diabetic retinopathy.

Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading

arXiv.org Machine Learning

Diabetes is a globally prevalent disease that can cause visible microvascular complications such as diabetic retinopathy and macular edema in the human eye retina, the images of which are today used for manual disease screening. This labor-intensive task could greatly benefit from automatic detection using deep learning technique. Here we present a deep learning system that identifies referable diabetic retinopathy comparably or better than presented in the previous studies, although we use only a small fraction of images ( 1/4) in training but are aided with higher image resolutions. We also provide novel results for five different screening and clinical grading systems for diabetic retinopathy and macular edema classification, including results for accurately classifying images according to clinical five-grade diabetic retinopathy and four-grade diabetic macular edema scales. These results suggest, that a deep learning system could increase the cost-effectiveness of screening while attaining higher than recommended performance, and that the system could be applied in clinical examinations requiring finer grading.

How Can We Be Sure Artificial Intelligence Is Safe For Medical Use?

NPR Technology

When Merdis Wells visited the diabetes clinic at the University Medical Center in New Orleans about a year ago, a nurse practitioner checked her eyes to look for signs of diabetic retinopathy, the most common cause of blindness. At her next visit, in February of this year, artificial intelligence software made the call. The clinic had just installed a system that's designed to identify patients who need follow-up attention. The Food and Drug Administration cleared the system -- called IDx-DR -- for use in 2018. The agency said it was the first time it had authorized the marketing of a device that makes a screening decision without a clinician having to get involved in the interpretation.

AI makes ophthalmologists more effective at detecting eye disease


Artificial intelligence holds the promise of diagnosing eye diseases faster and more accuracy than physicians. It is possible that technology could replace some of the more routine eye examinations hat physicians perform. While this may be the case, a new study indicates that the most effective application of advanced technology is with physicians and algorithms working in unison to track and detect eye diseases. The research builds upon developments from Google AI, which had shown that Google's health algorithm works almost as well as human medics when screening patients for the common diabetic eye disease called diabetic retinopathy (retinal vascular disease). The new research sought to inquire whether the algorithm could do more than simply diagnose disease.

3 ways AI is already changing medicine


When Dr. Eric Topol joined an experiment on using artificial intelligence to get personalized nutrition advice, he was hopeful. For two weeks, Topol, a cardiologist at Scripps Research, dutifully tracked everything he ate, wore a sensor to monitor his blood-glucose levels, and even collected and mailed off a stool sample for an analysis of his gut microbiome. The diet advice he got back stunned him: Eat Bratwurst, nuts, danishes, strawberries, and cheesecake. "It was crazy stuff," Topol told me. Bratwurst and cheesecake are foods Topol generally shirks because he considers them "unhealthy."

Indian American Kavya Kopparapu's AI Device for Brain Cancer Wins National STEM Award


The Indian American community has made its presence felt in different walks of life, including education, business and politics, even though they constitute only 1% of the total US population. In our last article in the series of stories about young Indians, we gave a shout-out to 17-year-old Jothi Ramaswamy from New York who, inspired by her engineer mother, holds workshops to push girls for STEM careers as part of her nonprofit'ThinkSTEAM'. Indian American Kavya Kopparapu has received the most coveted National STEM Education Award 2019 for her revolutionary invention having the sole objective of making treatments far more effective for glioblastoma, the most fatal form of brain cancer. Recognized as an extraordinarily talented and accomplished individual by STEM Education US, Kavya Kopparapu is a science whizz of Herndon, Virginia. A student of biology and computer science at Harvard University, Kavya has invented an AI technology-supported device named GlioVision that pictures characteristics of brain tumor in shorter time and at a lesser cost than the existing traditional methods.

First-of-its-Kind AI Tool for Diabetic Retinopathy Detection Approved by FDA


The AI-powered, cloud-based system will be available for use by primary care providers. Over 30 million Americans have diabetes, and diabetic retinopathy--which occurs when blood sugar levels result in damage to retinal blood vessels--is considered mostly preventable. Still, it causes vision loss in tens of thousands of people each year and is the leading cause of blindness among working-age Americans. "Many patients with diabetes are not adequately screened for diabetic retinopathy since about 50 percent of them do not see their eye doctor on a yearly basis," Malvina Eydelman, MD, said in the FDA's official announcement. She serves as director of the Division of Ophthalmic, and Ear, Nose and Throat Devices at the agency's Center for Devices and Radiological Health.

Google and Verily reveal algorithm for diabetic eye disease screening - MedCity News


Google and Verily, Alphabet's life sciences and healthcare arm, have created a machine learning algorithm to help screen for diabetic retinopathy and diabetic macular edema, according to a Google blog post. The development of the algorithm has been a three-year project, which also involved the organizations conducting a global clinical research program focused on India. Verily has received a CE mark for the algorithm. Now, they've revealed the first real-world clinical use of the algorithm is happening at Aravind Eye Hospital in Madurai, India. At the hospital, the process works like this: Technicians use a fundus camera to take one image of each of the patient's eyes.