Mount Sinai teams with RenalytixAI to employ AI and analytics for kidney disease care

Mount Sinai Health System and RenalytixAI announced that they will work together to commercialize artificial intelligence designed to improve kidney disease detection, management and treatment for patients with diabetes and other at-risk, large-scale patient populations. 

The partners will tap Mount Sinai’s data warehouse, which holds more than three million patient health records and 43,000 patient records in the BioMe BioBank repository.

With de-identified clinical data, the partners plan to create an advanced learning system to monitor and flag patients at risk for kidney disease and costly unplanned crashes into dialysis. They expect to introduce a product in the second quarter 2019 to address the $98 billion in preventable dialysis and chronic kidney disease costs.

“Our ability to apply the power of artificial intelligence against such a deep repository of clinical data in combination with prognostic biomarkers has the potential to change the game for all of our patients with diabetes and other populations at risk for kidney disease,” Barbara Murphy, MD, said in a statement. Murphy is dean for Clinical Integration and Population Health Management and chair for the Department of Internal Medicine at the Icahn School of Medicine at Mount Sinai. She also chairs the RenalytixAI Scientific Advisory Board.

“The fact that so many patients on dialysis have never seen a specialist has to change both from a patient care and cost perspective,” said RenalytixAI Executive Chairman Julian Baines.

Approximately 1 million patients cared for at Mount Sinai are either diagnosed with Type II diabetes or are of African ancestry, two of the major at-risk population segments for kidney disease.   

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