AI brain on a screen

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Diabetes is a disease that occurs because of the body’s inability to produce or use a vital elixir called insulin. Made by the pancreas, insulin helps absorb glucose and provides the body with energy to function.

There are two basic types of diabetes: Type 1, where the pancreas has been attacked by the body’s own immune system and is not able to produce any insulin at all; and type 2, which makes up over 90% of diabetes cases, where the body isn’t able to use insulin to breakdown glucose.

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In type 2 diabetes, too much insulin floating around in your body causes havoc. Diabetics suffer from poor blood circulation and are known to be in acute danger of heart attacks, strokes, amputations, blindness, and kidney problems. If you are overweight, obese, or not physically active, you are at a high risk of contracting type 2 diabetes.

But the odd thing about diabetes is that people who have it often don’t know, which is why the disease is referred to as a silent killer.

Around 37 million adult Americans, or 11.7% of the adult population, have type 2 diabetes, but only 28 million people in the US have been diagnosed with the disease. The rest don’t know they have it.

Globally, the picture is worse — 462 million people have type 2 diabetes, but at least half that number are unaware.

Testing times

You might think that, in our technology-fuelled age, innovators would have created a systematic, efficient, and affordable way to detect the presence of a commonplace disease like diabetes, which largely attacks the underprivileged. However, progress, until now, has been limited.

The most common test today still is one that measures blood glucose levels (called the Fasting Blood Glucose or FBG), which entails overnight fasting and a trip to a clinic, as does the increasingly popular glycated hemoglobin (A1C) test, which does not require fasting.

Unfortunately, for most of the world’s — and America’s — less fortunate, a clinic is sometimes not easily accessible, and the cost of the test can be higher than people can afford.

But what if you could use a device that almost everyone owns today to detect the disease, and at practically no cost? And instead of waiting for days to get the test result, it appeared straightaway?

This is the emerging promise of voice-based disease detectors, which are apps armed with AI engines that are beginning to deliver radical new ways of spotting disease using your smartphone and a voice sample of just a few seconds.

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Klick Health, a Toronto-based life science commercialization company, is one outfit that is looking to transform the process of detection and treatment with its pioneering test for diabetes.

The test is breathtakingly simple — it allows anyone with a smartphone to record their voice for just six to 10 seconds and find out whether they might have the disease.

Klick diagram

Klick says that its test for type 2 diabetes is better than the industry standard fasting blood glucose (FBG) type, but without the expense and inconvenience that FBG entails.

Klick Health

The company told ZDNET that it is going through a final round of replication studies this year before seeking regulatory approval.

The AI doc is always in

Welcome to the world of vocal biomarkers, where AI analyzes voice patterns and characteristics. Instead of needles and blood samples, the algorithm gauges the most minute shifts in speech or breath that aren’t discernable to mere mortals.

If the ‘old world’ uses human breath and a simulated cough as indicators to doctors of what might be awry under the hood, these vocal biomarkers dig deeper into tone and pitch, and a host of other markers.

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The frontrunner in the field today is Klick — and its voice-based diabetes test might foment a revolution in the early detection and successful treatment of diabetes.

In order to train and test out their AI-based solution, Jaycee Kaufman, a scientist at Klick labs, along with her team, recorded the voices of 267 individuals who either did not have diabetes or who had already been diagnosed with type 2 diabetes.

Over the course of two weeks, participants recorded a short sentence — “Hello, how are you? What is my glucose level right now?” — six times daily on their smartphones. This process generated over 18,000 voice samples, from which 14 acoustic features were singled out that differed in prevalence
or intensity across participants.

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The underpinning for Klick’s diabetes test is a change in the acoustic characteristics of a person’s voice because of the disease.

Diabetes, says Kaufman, tends to erode both nerves and muscles in men, impacting the robustness of their voices. On the other hand, women who have a higher correlation of depression or anxiety with diabetes tend to experience an increase in pitch.

Using these markers, Klick’s AI-powered model achieved startling accuracy. The model’s test for diabetes was 89% accurate when examining females, and 86% when assessing males — and there’s the likelihood the results will only get better over time.


Powered by AI, voice-based disease detection is poised to become one of the most popular ways we will begin to screen ourselves for a plethora of diseases.

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

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Machine learning is also being deployed to detect Parkinson’s disease, which relies on a method that hopes to introduce a screener for the disease with just a single sound of a patient saying “aaaaah.” This sound will be compared to a database of recordings of Parkinson’s patients and a control group.

However, while Klick’s voice-based test for diabetes is on par with lab tests in terms of accuracy, it is meant to be a first step toward the eventual diagnosis of diabetes.

All tests exhibit false positives and other errors. So, it is crucial for those who will use the test to reinforce findings with other conventional tests and a professional’s validation.

However, considering diabetes’ pernicious role in accelerating serious health problems, an early warning system in the shape of a voice test, which could save many lives and spur others to seek early treatment, is just what the doctor ordered.


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