2 Peer-Reviewed Publications — ML

2 Peer-Reviewed Publications — ML for Biomedical Classification

Co-authored two peer-reviewed papers on applied machine learning and deep learning in clinical and biological contexts, working with CNRS, CEA, and Université Côte d'Azur.

Paper 1 — Bioinformatics: Introduced PD-CR, a novel primal-dual classification method outperforming SVM, Random Forests, and PLS-DA on cancer metabolomics datasets (lung & brain tumors). Real clinical data from university hospitals of Nice and Montpellier.

Paper 2 — IEEE/ACM Transactions on Computational Biology and Bioinformatics: Non-invasive live cell cycle monitoring using a supervised autoencoder on Quantitative Phase Imaging data. Achieved 98.6% classification accuracy on 80,000+ cells.

Both projects used real clinical datasets. No simulations.