Benchmarking of Machine Learning Algorithms to Predict Mortality in Sepsis from Transcriptomic Data

Karishma Chhugani is pursuing her PhD in Pharmaceutical and Translational Sciences in which she is conducting bioinformatics research with Dr. Serghei Mangul and simultaneously is completing her Master’s in Management of Drug Development at USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences. She completed her thesis-based Master’s in Pharmaceutical Sciences from here as well in May 2021. She graduated from University of California, Riverside in June 2019 with a Bachelor’s of Science in Cellular, Molecular, and Developmental Biology. Currently, as part of her PhD projects, Karishma is creating a unified repository for robust, rigorous, and reproducible analysis of TCR-Seq data. In another project, she is benchmarking various machine learning algorithms to predict mortality in sepsis patients from gene expression and cell type composition data.
Abstract: drive.google.com/open?id=1xSw...