Yue Li, PhD - ITC4-2019 - Medicine Without Doctors?
Channel: Barbara Reney
Date: 2019-08-29

8. Clinical Recommendations by Means of Artificial Intelligence: The Example of MixEHR.  
MixEHR is an unsupervised generative model integrating collaborative filtering and latent topic models, which jointly models the distributions of data observation bias and actual data using latent disease-topic distributions. We apply MixEHR on 12.8 million phenotypic observations from 46,000 patients at the intensive care units (ICU) Beth Israel Deaconess Medical Center, and use it to reveal latent disease topics, interpret EHR results, impute missing data, and predict mortality in ICU. Using both simulation and real data, we show that MixEHR outperforms previous methods and reveals meaningful multi-disease insights. Additionally, we further extend MixEHR to investigating the relationship between genetically-regulated transcriptional variation and phenotypic variation in a cohort of 9400 inner-city, low-socioeconomic-status, primarily-African-American patients with Post traumatic stress disorder (PTSD) at the Grady Memorial Hospital. We found several noteworthy enrichments for well-studied genes and tissues in specific PTSD-related topics across multiple tissues.