Hassen A. Al-Amin

This study trains a variational autoencoder on metabolomics data to learn nonlinear latent representations and validates its generalizability across different disease cohorts.

This paper introduces a cutoff selection algorithm for correlation networks that uses prior knowledge to improve network reconstruction, showing better performance than statistical cutoffs across multiple datasets.