Quantitative abnormalities in the β-region of the electrophoretic profile of serum proteins as predictive markers of monoclonality: Machine learning for monoclonality prediction.

Journal: Clinical biochemistry

PMID: 39900216

Abstract

OBJECTIVE OF THE STUDY: To develop a machine learning algorithm aimed at predicting the presence of a monoclonal (M-) protein when the β-globulin fraction is elevated.

Authors

Sara Cherkaoui

Dept of Clinical Chemistry University Hospital Laboratory of Brussels (LHUB-ULB) Université Libre de Bruxelles Brussels Belgium. Electronic address: sara.cherkaoui@ulb.be.
Slavka Penickova

Dept of Clinical Chemistry University Hospital Laboratory of Brussels (LHUB-ULB) Université Libre de Bruxelles Brussels Belgium.
Frederic Cotton

Dept of Clinical Chemistry University Hospital Laboratory of Brussels (LHUB-ULB) Université Libre de Bruxelles Brussels Belgium.

Keywords

Adult Aged Algorithms Biomarkers Blood Protein Electrophoresis Blood Proteins Female Humans Machine Learning Male Middle Aged Paraproteinemias

External Resources

View on PubMed Access via DOI PubMed (39900216)

Quantitative abnormalities in the β-region of the electrophoretic profile of serum proteins as predictive markers of monoclonality: Machine learning for monoclonality prediction.

Abstract

Authors

Keywords

External Resources

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