As Artificial Intelligence (AI) grips our world and creates waves in numerous industries, there is perhaps no field that might benefit more from this advanced technology than the medical field.

Ten million new cases of dementia are diagnosed each year, but the presence of different dementia forms and overlapping symptoms can complicate diagnoses and the delivery of effective treatments.

According to the National Institutes of Health, more than 6 million older adults in the U.S. are living with dementia. What has medical experts perplexed though is the ability to spot the different types of dementia as some strains appear to go undetected.

This is where AI comes into the picture.

With this concern in mind, Mayo Clinic scientists are using AI and machine learning to analyze electroencephalogram (EEG) tests more quickly and precisely, enabling neurologists to find early signs of dementia among data that typically go unexamined.

In new research published in Brain Communications, scientists at the Mayo Clinic Neurology AI Program (NAIP) demonstrate how AI can not only speed up analysis but also alert experts reviewing the test results to abnormal patterns too subtle for humans to detect.

This groundbreaking technology shows the potential to one day help doctors distinguish among causes of cognitive problems, such as Alzheimer's disease and Lewy body dementia. The research suggests that EEGs, which are more widely available, less expensive, and less invasive than other tests to capture brain health, could be a more accessible tool to help doctors catch cognitive issues in patients early.

In addition to the work the scientists at Mayo Clinic are conducting, researchers at the University of Tsukuba and IBM Research identified, for the first time, a new way to recognize dementia.

What they discovered is that they can detect lower emotional expressivity in Lewy body dementia by quantifying vocal expression of emotions using deep neural network techniques.

Lewy body dementia is the second most prevalent neurodegenerative dementia after Alzheimer's disease. It progresses faster and has a broader range of symptoms compared with other forms of dementia, significantly decreasing patients’ quality of life.

However, because of overlapping symptoms with other diseases such as Alzheimer’s, and the limited availability of specialized physicians and facilities, Lewy body dementia often goes undiagnosed.

Catching it with AI may be the solution and researchers believe they may have cracked the problem.

Reduced emotional expression, a common symptom in patients with dementia, affects the quality of life by impairing daily communication and negatively impacting mental health. Despite its significance, there have been no objective and quantitative studies investigating emotional expression in individuals with Lewy body dementia.

Interestingly, in their new study published in Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, researchers collected voice recordings of people with Lewy body dementia and Alzheimer's disease while they read stories. They also collected recordings from older adults without cognitive impairments. Using a deep learning model, they analyzed the emotional tone of these voices.

The study found that people with Lewy body dementia showed more negative and calmer emotions and were less expressive overall compared to those with Alzheimer's and the healthy group. This was linked to cognitive decline and damage in a brain area called the insular cortex, common in Lewy body dementia.

The automated voice analysis showed promise in distinguishing people with Lewy body dementia from others based on their emotional expression.

The study has led researchers to believe that using deep neural networks to analyze vocal emotional expression can potentially facilitate early detection and delivery of appropriate care for Lewy body dementia.

Combining the Mayo Clinic’s AI method together with this recent study could have far-reaching potential.

With dementia cases set to double in the next 20 years, the question most interesting to researchers now is whether AI can provide accurate differential diagnoses for dementia and provide a promising pathway for targeted therapeutic interventions.