by RICH HARIDY
Researchers have developed models that could predict mild cognitive impairment and dementia with 88 percent accuracy PHOTO/lucidwaters/Depositphotos
A fascinating new study from a team of US researchers has used machine learning techniques to develop algorithms that can analyze naturalistic driving data and detect mild cognitive impairment and dementia in a driver. The work is still in the preliminary stages, however, the researchers claim it could be possible in the future to detect early signs of dementia using either a smartphone app or devices incorporated into car software systems.
The influence of dementia on driving behavior is a reasonably well-studied topic. It is certainly unsurprising to observe driving behaviors change as neurodegeneration leads to cognitive decline. However, this new research set out to explore whether machine learning techniques could be used to identify patterns in driving data that can then detect either mild cognitive impairment (MCI) or dementia.
The research utilized data from a novel long-term study called LongROAD (The Longitudinal Research on Aging Drivers), which tracked nearly 3,000 older drivers for up to four years, offering a large longitudinal dataset.
Over the course of the LongROAD study, 33 subjects were diagnosed with MCI and 31 with dementia. A series of machine learning models were trained on the LongROAD data, tasked with detecting MCI and dementia from driving behaviors.
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