Shahd ElNaggar

This study develops a machine learning model using oral microbiome data to predict esophageal squamous cell carcinoma, showing good performance across different geographic regions.

The paper identifies genomic alterations in the YAP/TAZ pathway associated with stem cell-like castration-resistant prostate cancer using transcriptomic and whole-genome sequencing data.

DEBIAS-M corrects processing bias in microbiome data, improving cross-study generalization of prediction models by learning interpretable bias-correction factors.