Pattern analysis based on fMRI data collected while subjects perform working memory tasks allowing high-precision diagnosis of ADHD. Hammer, R., Booth, J. R, Borhani, R., & Katsaggelos, A. K 2020.
Pattern analysis based on fMRI data collected while subjects perform working memory tasks allowing high-precision diagnosis of ADHD. [link]Paper  abstract   bibtex   
Using a plurality of distinct behavioral tasks conducted in a functional magnetic resonance imaging (fMRI) scanner, fMRI data acquired from one or more subjects performing working memory tasks can be used for diagnosing psychi atrics and neurological disorders. A classification algorithm can be used to determine a classification model, tune the model, and apply the model. An output indicative of a Subject's clinical condition can then be provided and used to diagnose new cases.
@unpublished{Reuven2020,
abstract = {Using a plurality of distinct behavioral tasks conducted in a functional magnetic resonance imaging (fMRI) scanner, fMRI data acquired from one or more subjects performing working memory tasks can be used for diagnosing psychi atrics and neurological disorders. A classification algorithm can be used to determine a classification model, tune the model, and apply the model. An output indicative of a Subject's clinical condition can then be provided and used to diagnose new cases.},
annote = {US Patent 10,571,539},
author = {Hammer, Rubi and Booth, James R and Borhani, Reza and Katsaggelos, Aggelos K},
title = {{Pattern analysis based on fMRI data collected while subjects perform working memory tasks allowing high-precision diagnosis of ADHD.}},
url = {https://patents.google.com/patent/US20170123028A1/en?inventor=Katsaggelos&num=100&oq=Katsaggelos&sort=old},
year = {2020}
}

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