(Image credit: Adobestock/Dragonstock)
The Icahn School of Medicine, Mount Sinai announced the launch of the Center for Ophthalmic Artificial Intelligence and Human Health, aimed at advancing artificial intelligence in the field of ophthalmology.
According to a news release from Mount Sinai,1 The center, the first of its kind in New York City, strives to reshape patient care by creating more timely diagnoses of eye disease and innovative risk assessments of general health conditions.
Mount Sinai is bringing AI to trainees and physicians’ education, research, and clinical settings to rapidly diagnose eye diseases and conditions. Eye diseases targeted for rapid diagnosis include macular degeneration, diabetic retinopathy, glaucoma, hypertensive retinopathy, systemic diseases, and retinal tumors.
Mount Sinai emphasized the importance of rapid diagnosis in a press release. “Some eye diseases are associated with cardiovascular and nervous system problems, so early detection and intervention can prevent vision loss, and can also prevent heart attacks and strokes.”
James C. Tsai, M.D., Professor Delafield Rogers, Director of Ophthalmology, Icahn Mount Sinai and Mount Sinai Health System, Director of the New York Mount Sinai Department of Eye and Ear and Throat (NYEE), and the first Director of the Center. talked about technology. Available at the Center for Ophthalmic Artificial Intelligence and Human Health.
“Our department is excited to be at the forefront of ophthalmic innovation in AI and human health, playing a key role in the validation and implementation of the most promising technologies,” said Tsai. “We expect this center to revolutionize and transform population-based health, thereby improving quality and equitable care. More timely diagnosis and referral of community-based eye diseases.” In addition, recent studies have shown that cardiovascular risk factors can be determined from AI-guided analysis of retinal fundus photography, thus allowing us to better predict future cardiovascular health. No other medicine allows us to observe and evaluate the vascular and nervous systems so unhindered.”
The center plans to implement AI models across three areas, including a retinal telemembrane program, an eye telemedicine program, and an eye stroke service.
The remote retinal program allows primary care physicians to upload retinal images taken with high-quality digital cameras to a technology platform, where NYEE retinal specialists can access the images for diagnosis.
The Remote Eye Consultation pilot program will provide patients with eye emergencies with rapid diagnosis using an advanced telemedicine platform. The program does not rely on face-to-face consultations with an ophthalmologist, providing a faster opportunity for treatment.1
In a press release, Dr. Thomas J. Fuchs, Dean of the Department of Artificial Intelligence and Human Health at Icahn Mount Sinai University, reiterated the importance of advancing AI.
“Artificial intelligence is revolutionizing our society, especially in the way we provide care to patients. We are on the front line: Mount Sinai enables us to realize our vision of AI-driven ophthalmology that will significantly improve care for virtually every patient that visits our hospital,” said Fuchs.
AI also plans to expand Mount Sinai’s Eye Stroke Service to expedite the diagnosis and treatment of patients suffering from acute eye stroke. High-resolution optical coherence tomography (OCT) retinal scans are now taken in several different emergency departments and sent to an on-call retinal specialist for immediate diagnosis and immediate stroke treatment with intra-arterial thrombolysis. alerting the neuroradiology team that .1
According to Mount Sinai, the researchers developed and used state-of-the-art AI algorithms to analyze these data-embedded images and translate these findings into the high-throughput genotyping data available at Icahn Mount Sinai. It is planned to be combined with
Dr. Mount-Sinai added that this would “inform the pathophysiology of eye disease, highlight medical disparities in eye disease, predict early disease onset and progression, better monitor disease and response to treatment, and provide a framework for better monitoring and treatment.” It will help develop unique ocular biomarkers that can provide Develop precision medicine strategies for these diseases and streamline the conduct of clinical trials. ”1
