Alzheimer's disease diagnosis by blood plasma molecular fluorescence spectroscopy (EEM).
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
28 09 2022
28 09 2022
Historique:
received:
23
06
2022
accepted:
15
09
2022
entrez:
28
9
2022
pubmed:
29
9
2022
medline:
1
10
2022
Statut:
epublish
Résumé
Despite tremendous research advances in detecting Alzheimer's disease (AD), traditional diagnostic tests remain expensive, time-consuming or invasive. The search for a low-cost, rapid, and minimally invasive test has marked a new era of research and technological developments toward establishing blood-based AD biomarkers. The current study has employed excitation-emission matrices (EEM) of fluorescence spectroscopy combined with machine learning to diagnose AD using blood plasma samples from 230 individuals (83 AD patients from 147 healthy controls). To evaluate the performance of the classification algorithms, we calculated the commonly used figures of merit (accuracy, sensitivity and specificity) and figures of merit that take into account the samples unbalance and the discrimination power of the models, as F
Identifiants
pubmed: 36171258
doi: 10.1038/s41598-022-20611-y
pii: 10.1038/s41598-022-20611-y
pmc: PMC9519548
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
16199Informations de copyright
© 2022. The Author(s).
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