Digital Commons Network^™

Predicting Patient Outcomes With Machine Learning For Diverse Health Data, Dingwen Li

McKelvey School of Engineering Theses & Dissertations

As digitized clinical and health data become ubiquitous, machine learning techniques have shown promise in predicting various clinical outcomes. In this thesis research, we exploit three types of data including (1) data collected through wearables outside hospitals, (2) electronic health records (EHR) data of inpatient in general hospital wards, (3) intraoperative data collected during surgery. This thesis work investigates machine learning approaches for the diverse clinical and health data with distinctive characteristics and challenges in the context of real-world clinical applications. Specifically, this thesis makes the following contributions to the state of the art of clinical machine learning.

Extracting informative …

Assessment And Diagnosis Of Human Colorectal And Ovarian Cancer Using Optical Imaging And Computer-Aided Diagnosis, Yifeng Zeng

McKelvey School of Engineering Theses & Dissertations

Tissue optical scattering has recently emerged as an important diagnosis parameter associated with early tumor development and progression. To characterize the differences between benign and malignant colorectal tissues, we have created an automated optical scattering coefficient mapping algorithm using an optical coherence tomography (OCT) system. A novel feature called the angular spectrum index quantifies the scattering coefficient distribution. In addition to scattering, subsurface morphological changes are also associated with the development of colorectal cancer. We have observed a specific mucosa structure indicating normal human colorectal tissue, and have developed a real-time pattern recognition neural network to localize this specific structure …