Health start-up Medial EarlySign is utilising machine learning to support diabetic patients

By Catherine Sturman
Located in Kfar Malal, Israel, healthcare start-up Medial EarlySign has worked to develop a machine-learning solution to provide a long-term solution to...

Located in Kfar Malal, Israel, healthcare start-up Medial EarlySign has worked to develop a machine-learning solution to provide a long-term solution to diabetes patients. The technology will support the ongoing management of diabetes, improve clinical data and provide better patient outcomes.

Recent clinical data has highlighted and identified patients who are most at risk of having renal dsyfunction after just one year. The technology has analysed a number of areas within Electronic Health Records (EHRs), including laboratory tests results, demographics, medication, diagnostic codes and many more, to enable the prediction of those who are most at risk.

By isolating less than 5% of the 400,000-diabetic population selected among the company's database of 15 million patients, the algorithm was able to identify 45% of patients who would progress to significant kidney damage within a year, prior to becoming symptomatic. Kidney problems are one of the most common symptoms of diabetes-related complications.

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"Immense efforts are invested in developing treatment protocols to reduce the number of patients who will develop renal dysfunction due to diabetes," said Dr. Ran Goshen, Medial EarlySign's Chief Medical Officer.

"Medial EarlySign's algorithm can aid decision-makers, drug developers, insurers and providers to better allocate their capped resources and secure preferential clinical outcome as well. This can help reduce the likelihood for diabetes related end stage renal disease (ESRD)."

By leveraging EHR data, medical professionals can widen their clinical knowledge and expertise, redefine the management of chronic diseases, improve patient outcomes and lower healthcare costs.

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