Diagnosing Alzheimer’s Early on with Machine Learning


Diagnosing Alzheimer’s early on has been a challenge that physicians and other experts continue to battle out. However, with technological advancements today, the dilemma may be detectable at all – even in its initial stage.

Researchers from VU University Medical Centre in Amsterdam, with Dr. Alle Meije Wink at the forefront, utilized machine-learning devices to identify early forms of the disease through a special MRI scan. The scan will then be showing the amount of blood going to the various areas of the brain. The scientists studied data and were able to classify 60 with mild cognitive impairment, 100 most likely to have Alzheimer’s, 100 with subjective cognitive decline, and 26 healthy. The machine-learning tool, thus was not only capable of grouping patients according to their levels of cognitive impairment but was also able to tell if one had the disease in past undiagnosed cases.

Good news indeed for those whose loved ones are at the brink of incurring the disease! Good thing there are also home care services at their disposal – making excellent health care just some fingertips away.

— Image Courtesy of Pixabay

Featured Posts
Recent Posts
Search By Tags
Follow Us
  • Facebook Basic Square
  • Twitter Basic Square
  • Google+ Basic Square
  • Facebook Social Icon
  • Twitter Social Icon
  • Google+ Social Icon

Palo Alto - Los Altos - Menlo Park - Atherton - Mountain View - Sunnyvale - Hillsborough - Portola Valley - Woodside
San Jose - Saratoga - Los Gatos - Santa Clara - Cupertino - Campbell - Monte Sereno - Gilroy - Morgan Hill
San Mateo - Redwood City - Burlingame - San Carlos - San Bruno - Belmont - Millbrae - Foster City - Daly City - Brisbane 
Walnut Creek - Danville - Orinda - Lafayette - Moraga - Concord - San Ramon - Pleasant Hill - Brentwood - Martinez - El Cerrito 
Pleasanton - Fremont - Oakland - Dublin - Milpitas - Newark - Piedmont - Berkeley - San Leandro - Union City - Hayward - Emeryville

Copyright 2018 Homecare California, Inc.

All rights reserved.

LIC# 434700006