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Development and internal validation of a diagnostic prediction model for psoriasis severity
Mie Sylow Liljendahl
,
Nikolai Loft
,
Alexander Egeberg
,
Lone Skov
, Tri-Long Nguyen
Dermatology and Allergy
Dermatology, Department of
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Dive into the research topics of 'Development and internal validation of a diagnostic prediction model for psoriasis severity'. Together they form a unique fingerprint.
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Keyphrases
Diagnostic Model
100%
Moderate-to-severe Psoriasis
100%
Bootstrap
100%
Internal Validation
100%
Psoriasis Severity
100%
Development Validation
100%
Diagnostic Prediction Model
100%
National Registry
66%
C-statistic
66%
Epidemiology
33%
Register Data
33%
Disease Severity
33%
Registry-based
33%
Psoriasis
33%
Psoriasis Disease
33%
Discrimination Power
33%
Machine Learning Techniques
33%
Gradient Boosting Machine
33%
Administrative Register Data
33%
Underfitting
33%
Bootstrap Correction
33%
Gradient Boosting
33%
Administrative Health Records
33%
Boosting Learning
33%
Psychology
Psoriasis
100%
Discrimination
14%
Biochemistry, Genetics and Molecular Biology
Cohort Study
100%