oru.sePublikationer
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
The PredictAD project: development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease.
Show others and affiliations
2013 (English)In: Interface Focus, ISSN 2042-8898, E-ISSN 2042-8901, Vol. 3, no 2, 20120072Article in journal (Refereed) Published
Abstract [en]

Alzheimer's disease (AD) is the most common cause of dementia affecting 36 million people worldwide. As the demographic transition in the developed countries progresses towards older population, the worsening ratio of workers per retirees and the growing number of patients with age-related illnesses such as AD will challenge the current healthcare systems and national economies. For these reasons AD has been identified as a health priority, and various methods for diagnosis and many candidates for therapies are under intense research. Even though there is currently no cure for AD, its effects can be managed. Today the significance of early and precise diagnosis of AD is emphasized in order to minimize its irreversible effects on the nervous system. When new drugs and therapies enter the market it is also vital to effectively identify the right candidates to benefit from these. The main objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data, electrophysiological measurements of the brain and structural, functional and molecular brain images. We also designed and built a statistical model and a framework for exploiting these biomarkers with other available patient history and background data. We were able to discover several potential novel biomarker candidates and implement the framework in software. The results are currently used in several research projects, licensed to commercial use and being tested for clinical use in several trials.

Place, publisher, year, edition, pages
2013. Vol. 3, no 2, 20120072
Keyword [en]
Alzheimer's disease, clinical decision support systems, early diagnosis
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:oru:diva-63678DOI: 10.1098/rsfs.2012.0072PubMedID: 24427524OAI: oai:DiVA.org:oru-63678DiVA: diva2:1169243
Available from: 2017-12-22 Created: 2017-12-22 Last updated: 2017-12-22

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed
By organisation
School of Medical Sciences
In the same journal
Interface Focus
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf