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August 7, 2025Expert Review of Proteomics

A 2025 perspective on the role of machine learning for biomarker discovery in clinical proteomics

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Authors

CACharlotte AdamsWBWout Bittremieux

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Overview

Perspective highlights challenges in biomarker discovery through machine learning in clinical proteomics, suggesting better practices.

Key Points

  • Machine learning shows promise for biomarker discovery but faces limitations in clinical proteomics.
  • Common issues like overfitting and data leakage hinder machine learning models in real-life applications.
  • Adopting simpler models may yield better interpretability and performance compared to complex architectures.
  • Emphasizing rigorous design and validation can enhance the translational impact of machine learning in clinical settings.

Cite This Study

Adams et al. (2025) studied this question.

synapsesocial.com/papers/689dfe90d61984b91e13bb3fhttps://doi.org/10.1080/14789450.2025.2545828
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