Faculty Lead(s)

Meliha Yetisgen


Clinical Informatics

Project Summary

Clinical and translational research involving critical illness phenotypes relies heavily on the identification of clinical syndromes defined by consensus definitions (e.g. pneumonia, sepsis, acute lung injury). The overall goal of this project is to apply natural language processing, machine learning, and network analysis to develop an automated screening tool that accurately identifies critical illness phenotypes and their interactions among ICU patients.