Claims and electronic health record (EHR) data are known sources of real-world healthcare data — neither of which were created for real-world evidence (RWE) generation — but have proved effective in deeply understanding the patient journey. More recently, it has become evident that medical images, from histopathology slides, X-rays, CT scans to MRI scans and ophthalmic images, can offer RWE insights as well when linked with sources such as claims and EHR. Ophthalmic images, for example, capture fluid levels, lesion growth and visual field, all of which are critical in an ophthalmologist’s diagnosis, treatment and care decisions. These variables are just as relevant for researchers to identify patients for a clinical trial, track disease progression within patient populations or understand how patient groups responded to a certain treatment. Imaging is a critical part of care and has untapped potential when linked with a data source such as EHR data that reveals other key patient demographics and characteristics. In order to use these images as a source of real-world data (RWD) — all of which exist in different formats — researchers are applying machine learning (ML) techniques and developing algorithms to label and recognize patterns. Join this webinar to learn about the power of images, specifically ophthalmic images, and how linking them with EHR data and applying ML can help support patient journey and disease progression research. Bonus: Hear use cases for imaging that include support for clinical trials, optimized dosing schedules and comparative effectiveness studies.
25 Jan 2023, 1:00 pm - 2:00 pm

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