Machine Learning

Verana Health to Present three abstarcts at ARVO 2022 Meeting

Research developed using Ophthalmology Qdata™, quality real-world data stemming from the American Academy of Ophthalmology IRIS® Registry

Verana Health®—a digital health data company elevating quality in real-world data—today announced three abstracts are to be presented at the Association for Research in Vision and Ophthalmology’s (ARVO) 2022 Annual Meeting, which will be held in Denver May 1-4.

The research findings were generated through analysis of Ophthalmology Qdata®, quality real-world data resulting from the curation of the American Academy of Ophthalmology IRIS® Registry (Intelligent Research in Sight). The IRIS Registry—powered by Verana Health’s VeraQ™ population health data engine—is the nation’s first and the world’s largest electronic health record-based registry on comprehensive eye disease and conditions. It incorporates data on nearly 74 million patients and more than 440 million billable visits. These data have been contributed by nearly 3,000 participating ophthalmology practices across the U.S.

The three research abstracts being presented at ARVO demonstrate Verana Health’s commitment to collaborating with life sciences companies to uncover new insights from its exclusive real-world data network of more than 20,000 healthcare providers.

M. Ali Khan, M.D., will present a virtual poster abstract about a study conducted in collaboration with Apellis Pharmaceuticals,  titled “Retrospective cohort analysis of patients with geographic atrophy (GA) secondary to age-related macular degeneration followed for 3 years in clinical practice” in a session on Sunday, May 1 from 11:15 a.m. to 1:15 p.m. PDT. Findings from this retrospective study of a large real-world database showed that GA caused substantial disease burden. Eyes with GA lost significant vision over a 3-year period, consistent with trends in the previously reported 2-year analysis. The rate of vision loss was numerically similar regardless of whether lesions were non-subfoveal or subfoveal at baseline. Eyes with good vision at baseline lost more letters over 3 years compared to eyes with poor vision.

Zhongdi Chu, Ph.D., will present an in-person Verana Health-led poster abstract titled “Automated machine learning for diagnosis of GA and subfoveal involvement using real-world fundus autofluorescence and infrared reflectance images” during a session on Sunday, May 1 from 4:15 p.m. to 6:15 p.m. PDT. The presentation will discuss a study examining the development of a machine learning pipeline that automatically uses real-world imaging data to diagnose and stage patients with GA, a condition that impairs visual function and patient quality of life. To execute the study, researchers developed a machine learning-aided pipeline for the IRIS Registry, using a de-identified clinico-imaging dataset of patients with dry age-related macular degeneration (AMD) contributed by two large retina practices. Researchers concluded that the method could potentially be useful in screening patients for future GA trials and treatments.

Theodore Leng, M.D., M.S., will present an in-person poster abstract conducted in collaboration with Apellis Pharmaceuticals, titled “Characterizing real-world functional outcomes in patients with GA: An IRIS Registry Analysis” in a session on Monday, May 2 from 11:30 a.m. to 1:30 p.m. PDT. GA represents the advanced form of dry AMD, accounts for one-third of the cases of late AMD, and is responsible for 20% of cases of severe visual loss due to the disorder. However, real-world data on correlations between lesion progression and functional decline are lacking. To address this gap, researchers performed a retrospective cohort analysis of patient notes to assess the feasibility of quantifying vision-related quality of life and patient-reported outcomes in GA.

To schedule a meeting with a representative of Verana Health at ARVO, click here

For more such updates and perspectives around Digital Innovation, IoT, Data Infrastructure, AI & Cybersecurity, go to AI-Techpark.com.

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