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International Competition on Mass Spectrometry Proteomic Diagnosis
Case-Control Breast Cancer Study of MALDI-TOF Proteomic Mass Spectrometry Data on Serum Samples
Organizing a Competition on Clinical Mass Spectrometry Based Proteomic Diagnosis
Application of the Random Forest Classification Method to Peaks Detected from Mass Spectrometric Proteomic Profiles of Cancer Patients and Controls*
Developing a Discrimination Rule between Breast Cancer Patients and Controls Using Proteomics Mass Spectrometric Data: A Three-Step Approach *
Principal Component Discriminant Analysis
Classification of Breast Cancer versus Normal Samples from Mass Spectrometry Profiles Using Linear Discriminant Analysis of Important Features Selected by Random Forest*
A Classification Model for the Leiden Proteomics Competition
Empirical Bayes Logistic Regression
Autocorrelated Logistic Ridge Regression for Prediction Based on Proteomics Spectra
Support Vector Machine Approach to Separate Control and Breast Cancer Serum Samples
A Cross-Validation Study to Select a Classification Procedure for Clinical Diagnosis Based on Proteomic Mass Spectrometry *
Clinical Mass Spectrometry Proteomic Diagnosis by Conformal Predictors *
Assessing the Validity Domains of Graphical Gaussian Models in Order to Infer Relationships among Components of Complex Biological Systems
Breast Cancer Diagnosis from Proteomic Mass Spectrometry Data: A Comparative Evaluation