Pregled bibliografske jedinice broj: 759095
Multilayer clustering: Biomarker driven segmentation of Alzheimer's disease patient population
Multilayer clustering: Biomarker driven segmentation of Alzheimer's disease patient population // Bioinformatics and Biomedical Engineering / Ortuno, Francisco ; Rojas, Ignacio (ur.).
Heidelberg: Springer, 2015. str. 134-145 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 759095 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Multilayer clustering: Biomarker driven segmentation of Alzheimer's disease patient population
Autori
Gamberger, Dragan ; Ženko, Bernard ; Mitelpunkt, Alexis ; Lavrač, Nada
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Bioinformatics and Biomedical Engineering
/ Ortuno, Francisco ; Rojas, Ignacio - Heidelberg : Springer, 2015, 134-145
ISBN
978-3-319-16482-3
Skup
International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2015)
Mjesto i datum
Granada, Španjolska, 15.04.2015. - 17.04.2015
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Data clustering; Alzheimer's disease; Biomarker identification
Sažetak
Identification of biomarkers for the Alzheimer's disease is a challenge and a very difficult task both for medical research and data analysis. In this work we present results obtained by application of a novel clustering tool. The goal is to identify subpopulations of the Alzheimer's disease (AD) patients that are homogeneous in respect of available clinical and biological descriptors. The result presents a segmentation of the Alzheimer's disease patient population and it may be expected that within each subpopulation separately it will be easier to identify connections between clinical and biological descriptors. Through the evaluation of the obtained clusters with AD subpopulations it has been noticed that for two of them relevant biological measurements (whole brain volume and intracerebral volume) change in opposite directions. If this observation is actually true it would mean that the diagnosed severe dementia problems are results of different physiological processes. The observation may have substantial consequences for medical research and clinical trial design. The used clustering methodology may be interesting also for other medical and biological domains.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-IP-2013-11-9623 - Postupci strojnog učenja za dubinsku analizu složenih struktura podataka (DescriptiveInduction) (Gamberger, Dragan, HRZZ - 2013-11) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb
Profili:
Dragan Gamberger
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus