Early alzheimer's disease progression detection using multi-subnetworks of the brain

Jaroslav Rokicki, Hiyoshi Kazuko, Francois Benoit Vialatte, Andrius Usinskas, Andrzej Cichocki

Результат исследований: Глава в книге, отчете, сборнике статейМатериалы для конференциирецензирование

Аннотация

Alzheimer's disease is neurodegenerative disorder believed to affect 24.3 million people worldwide. Proposed MRI based disease progression markers have shown ability to perform the classification between the Alzheimer's Disease (AD), Mild Cognitive Impariment (MCI) and Normal Cognitive (NC) subjects. We exploited two approaches, first one is to use single sub-network volume as a feature, second to use a network of most discriminative sub-networks. Multi-feature approach showed improvement by 4.5% in AD/NC classification case, and 1.5 % in MCI/NC case. Study was summarized for 48 AD, 119 MCI and 66 NC subjects.

Язык оригиналаАнглийский
Название основной публикацииIJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence
Страницы684-691
Число страниц8
СостояниеОпубликовано - 2012
Опубликовано для внешнего пользованияДа
Событие4th International Joint Conference on Computational Intelligence, IJCCI 2012 - Barcelona, Испания
Продолжительность: 5 окт. 20127 окт. 2012

Серия публикаций

НазваниеIJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence

Конференция

Конференция4th International Joint Conference on Computational Intelligence, IJCCI 2012
Страна/TерриторияИспания
ГородBarcelona
Период5/10/127/10/12

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