Machine Learning Finds New Risk Factors for Dementia
Machine learning, a hot field in computer programming, uses artificial intelligence (AI) to “teach” computers how to analyze data on their own — without additional human intervention. AI is currently being used in every field, from cybersecurity to the development of self-driving cars. So it should come as no surprise that machine learning is also being used to detect patterns within a variety of diseases.
The first study to use machine learning to analyze dementia risk was published in the Journal of Alzheimer’s Disease. Although the technology is cutting-edge, the data set it used is one of the oldest and most respected in the country: the Framingham Heart Study (FHS). The FHS, which turns 71 this year, began in 1948 with a cohort of just over 5000 men and women from Framingham, Massachusetts. Under the directive of the National Heart, Lung and Blood Institute, it has followed three generations of Framingham residents, and producing a wealth of data about cardiovascular disease.
That huge pool of data is useful for other diseases as well. The Boston University School of Medicine turned to FHS in its quest to uncover risk factors for dementia, especially risk factors that can be identified well before dementia shows its symptoms.
The study also sought factors that could be identified by laymen, rather than the specialty screening that is available today. The fact that today only a neurologist with advanced training can test for dementia means that few people have access to testing. Typically, even those who do get tested have symptoms that are significant.
That’s not the best approach, according to the researchers. “The frontline for screening are primary care physicians or family members,” explains Prof. Rhoda Au, one of the study’s authors. “We wanted to identify information that any physician or even non-physician has easy access to in determining potential increased future risk for dementia.”
What did the study find? Older age was obviously a significant risk factor, but other, less obvious associations were also found. A lower BMI, normally indicative of good health, was associated with dementia, as were being widowed, and having had a less-than-average amount of sleep between the ages of 40 and 60.
Although the mechanisms behind these risk factors are not understood, knowledge of their existence can already inform clinical decisions. If a widow or widower is underweight or has a history of sleeplessness, they can be watched for early signs of cognitive change. These simple, readily observed factors can alert family and doctors to subtle cognitive changes that will only later manifest as full-blown dementia. And that is where this will make a difference. Treating dementia at its earliest stages allows it to be managed with the greatest success.
At Laurel Bay Health and Rehabilitation Center, in Keansburg, NJ, our residents receive the highest quality rehabilitative and skilled nursing care in a homelike and compassionate environment conducive to healing.
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