Mahsa Monshizadeh

This study develops confounder-free predictive models for host phenotype prediction using microbiome data, showing improved accuracy and biological interpretability.

The paper introduces MicroKPNN-MT, a model that predicts human phenotypes and missing metadata from microbiome data, improving disease prediction accuracy and model generalizability.

The paper introduces MicroKPNN, a microbiome-based predictive model that improves host phenotype prediction by incorporating metabolic activity, taxonomy, and community structure, outperforming existing methods in multiple diseases.