New Computerized Linguistic Approach Developed to Detect Alzheimer’s Disease
In a study led by researchers from the Toronto Rehabilitation Institute, researchers developed a technique to diagnose Alzheimer’s disease with more than 82-percent accuracy by evaluating the interplay between four linguistic factors and by developing automated technology to detect these impairments. Based on the analysis, it was determined that four collective dimensions of speech are indicative of dementia: semantic impairment, such as using overly simple words; acoustic impairment, such as speaking more slowly; syntactic impairment, such as using less complex grammar and information impairment, such as not clearly identifying the main aspects of a picture. “Previous to our study, language factors were connected to Alzheimer’s disease, but often only related to delayed memory or a person’s ability to follow instructions,” said one of the study’s researchers. “This study characterizes the diversity of language impairments experienced by people with Alzheimer’s disease, and our automated detection algorithm takes this into account.” To read more about this study, click here.
2017 National Neuroscience Review
March 31-April 1, 2017; National Harbor, Md.
Brain & Brain PET 2017
April 1-4, 2017; Berlin, Germany
Neurosurgical Society of America Annual Meeting 2017
April 2-5, 2017; Jacksonville, Fla.
13th Head & Neck Cancer Symposium
April 6-7, 2017; Amsterdam, The Netherlands
Endoscopic and Endoscope-Assisted Neurosurgery Under FULL HD Visualization
April 6-7, 2017; Germany