Mount Sinai Health Systems Uses Artificial Intelligence to Identify Kidney Disease

Mount Sinai Health Systems Uses Artificial Intelligence to Identify Kidney Disease

Kidney disease is the ninth leading cause of death in the United States, affecting an estimated 31 million people. When patients reach stage 4 of chronic kidney failure they are required to undergo dialysis. The expected lifespan for patients on dialysis is between 5 and 10 years. However, life expectancy can be greatly increased if kidney disease is detected early and preventative steps are taken to slow the progression of the disease.

An estimated one in three American adults are at risk of developing kidney disease, but the condition is under diagnosed.  A significant minority of patients never see a nephrologist prior to starting dialysis. When ‘crash’ dialysis is required, patients have a much lower survival rate than if dialysis is planned. With early detection, patients at risk can be identified, thus avoiding the need for crash dialysis.

Mount Sinai Health System is now taking steps to improve the diagnosis of the disease and to help with the identification of patients at risk the health system will be using an artificial intelligence system.

Mount Sinai Health System has teamed up with Renalytix AI and will be providing the KF Diagnostics subsidiary with its data assets to train its AI system to identify patients with kidney disease and those most at risk of developing the disease. Mount Sinai Health System has more than 3 million patient records and the data of 43,000 biobank participants, which will be used to train the AI system.

The health system also plans to recruit other U.S health systems and feed their data into the system. The aim is to have a working version of the AI system ready to be commercialized by the second quarter of 2019.

The system will be trained to look for prognostic biomarkers and will issue alerts when patients are identified as having kidney disease or when it looks likely that crash dialysis would be required. It is hoped the system will help to significantly improve patient outcomes.

Barbara Murphy, M.D., dean for clinical integration and population health management at the Icahn School of Medicine at Mount Sinai, said “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.”

Leave a Reply