Operations Research, Systems Engineering and Industrial Engineering Commons^™

Early Detection Of Disease Using Electronic Health Records And Fisher's Wishart Discriminant Analysis, Sijia Yang, Jian Bian, Zeyi Sun, Licheng Wang, Haojin Zhu, Haoyi Xiong, Yu Li

Engineering Management and Systems Engineering Faculty Research & Creative Works

Linear Discriminant Analysis (LDA) is a simple and effective technique for pattern classification, while it is also widely-used for early detection of diseases using Electronic Health Records (EHR) data. However, the performance of LDA for EHR data classification is frequently affected by two main factors: ill-posed estimation of LDA parameters (e.g., covariance matrix), and "linear inseparability" of the EHR data for classification. To handle these two issues, in this paper, we propose a novel classifier FWDA -- Fisher's Wishart Discriminant Analysis, which is developed as a faster and robust nonlinear classifier. Specifically, FWDA first surrogates the distribution of "potential" inverse …

Venous Thromboembolism (Vte) Harm Measurement And Risk Assessment In Real-Time Using Electronic Health Records(Ehr), Seyed Mani Marashi

Wayne State University Dissertations

Venous Thromboembolism (VTE) is a deadly disease and is considered as one of the top reasons for avoidable hospital deaths in the United States and around the world. Patients who survive this disease often must face life-long complications such as Post-thrombotic syndrome (PTS), Chronic thromboembolic pulmonary hypertension (CTPH), etc. Therefore, it is important to monitor and reduce the number of VTE instances in hospitals. This study shows how Electronic Health Records (EHRs) can be utilized to achieve this goal.

First, a new near real-time VTE harm measurement model was developed. Not only the developed model can deliver near real-time results, …