Expert-level detection of M-proteins in serum protein electrophoresis using machine learning.

ABSTRACT:

Objectives

Serum protein electrophoresis (SPE) in combination with immunotyping (IMT) is the diagnostic standard for detecting monoclonal proteins (M-proteins). However, interpretation of SPE and IMT is weakly standardized, time consuming and investigator dependent. Here, we present five machine learning (ML) approaches for automated detection of M-proteins on SPE on an unprecedented large and well-curated data set and compare the performance with that of laboratory experts.

Methods

SPE and IMT were performed in serum samples from 69,722 individuals from Norway. IMT results were used to label the samples as M-protein present (positive, n=4,273) or absent (negative n=65,449). Four feature-based ML algorithms and one convolutional neural network (CNN) were trained on 68,722 ra

SUBMITTER: Elfert E 

PROVIDER: S-EPMC11470231 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature