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Statistical strategies and stochastic predictive models for the MARK-AGE data
- Publication Year :
- 2015
-
Abstract
- MARK-AGE aims at the identification of biomarkers of human aging capable of discriminating between the chronological age and the effective functional status of the organism. To achieve this, given the structure of the collected data, a proper statistical analysis has to be performed, as the structure of the data are non trivial and the number of features under study is near to the number of subjects used, requiring special care to avoid overfitting. Here we described some of the possible strategies suitable for this analysis. We also include a description of the main techniques used, to explain and justify the selected strategies. Among other possibilities, we suggest to model and analyze the data with a three step strategy
- Subjects :
- Male
Aging
Databases, Factual
Computer science
Biological age
Biomarkers, Biological age, Chronological age, Statistics models, MARK-AGE
Overfitting
Machine learning
computer.software_genre
03 medical and health sciences
0302 clinical medicine
ddc:570
Humans
Statistical analysis
Organism
030304 developmental biology
Structure (mathematical logic)
Electronic Data Processing
Stochastic Processes
0303 health sciences
Statistics model
business.industry
Chronological age
Biomarker
Models, Theoretical
MARK-AGE
Ageing
Female
Identification (biology)
Functional status
Special care
Artificial intelligence
business
computer
030217 neurology & neurosurgery
Developmental Biology
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....2250d752be79d16fa273f516b125fa33