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Researchers develop algorithms for early detection of mild cognitive impairment and dementia using naturalistic driving data


Researchers develop algorithms for early detection of mild cognitive impairment and dementia using naturalistic driving data
Using naturalistic driving data and machine learning techniques, researchers at Columbia University Mailman School of Public Health and Columbia’s Fu Foundation School of Engineering and Applied Science have developed highly accurate algorithms for detecting mild cognitive impairment and dementia in older drivers.
Naturalistic driving data refer to data captured through in-vehicle recording devices or other technologies in the real-world setting. These data could be processed to measure driving exposure, space and performance in great detail. The open-access findings are published in the journal ....

Foundation For Traffic Safety , Columbia University Mailman School Of Public Health , Longitudinal Research On Aging Drivers Long , Columbia Fu Foundation School Of Engineering , Columbia University Mailman School , Public Health , Applied Science , Longitudinal Research , Aging Drivers , அடித்தளம் க்கு போக்குவரத்து பாதுகாப்பு , கொலம்பியா பல்கலைக்கழகம் மெயில்மேன் பள்ளி ஆஃப் பொது ஆரோக்கியம் , கொலம்பியா ஃபூ அடித்தளம் பள்ளி ஆஃப் பொறியியல் , கொலம்பியா பல்கலைக்கழகம் மெயில்மேன் பள்ளி , பொது ஆரோக்கியம் , பயன்படுத்தப்பட்டது அறிவியல் , நீளமான ஆராய்ச்சி ,

Driving behaviors harbor early signals of dementia


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April 28, 2021 Using naturalistic driving data and machine learning techniques, researchers at Columbia University Mailman School of Public Health and Columbia s Fu Foundation School of Engineering and Applied Science have developed highly accurate algorithms for detecting mild cognitive impairment and dementia in older drivers. Naturalistic driving data refer to data captured through in-vehicle recording devices or other technologies in the real-world setting. These data could be processed to measure driving exposure, space and performance in great detail. The findings are published in the journal
Geriatrics.
The researchers developed random forests models, a statistical technique widely used in AI for classifying disease status, that performed exceptionally well. Based on variables derived from the naturalistic driving data and basic demographic characteristics, such as age, sex, race/ethnicity and education level, we could predict mild cognitive i ....

United States , Lisa Molnar , Thelmaj Mielenz , Minjae Kim , Howard Andrews , Terry Goldberg , Barbara Lang , David Strogatz , Carolyn Diguiseppi , Linda Hill , Vagelos College Of Physicians , Foundation For Traffic Safety , Bassett Research Institute , Columbia Vagelos College Of Physicians , Longitudinal Research On Aging Drivers Long , Columbia Mailman School Of Public Health , Columbia University Mailman School Of Public Health , University Of Michigan Transportation Research Institute , Colorado School Of Public Health , Columbia Fu Foundation School Of Engineering , Columbia University Mailman School , Public Health , Applied Science , Columbia Engineering , Longitudinal Research , Aging Drivers ,