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which relies on a method that hopes to introduce a screener for the disease with just a single sound of a patient saying aaaaah.it is meant to be a first step toward the eventual diagnosis of diabetes.

Klicks AI-powered model achieved startling accuracy.But the odd thing about diabetes is that people who have it often dont know.which largely attacks the underprivileged.

but only 28 million people in the US have been diagnosed with the disease.But what if you could use a device that almost everyone owns today to detect the disease.

a group of 10 universities have been given funding to explore using AI to detect changes in voice to discover Alzheimers disease and autism via a low-cost diagnostic tool.

recorded the voices of 267 individuals who either did not have diabetes or who had already been diagnosed with type 2 diabetes.write Danilo Pietro Pau and Fabrizio Maria Aymone.

Google introduced a radically scaled-down AI approach called TinyML several years ago. That effort takes far more processing power.

A signature effort there is MITs TinyTL. The greater challenge for technology companies is to make those kinds of neural networks not just perform predictions on a phone.