SRL MS Thesis Defense of Seth Polsley. Monday, June 5. Title: Identifying Outcomes of Care from Medical Records to Improve Doctor-Patient Communication

Thesis Defense
Monday, June 5

Title: 

Identifying Outcomes of Care from Medical Records to Improve Doctor-Patient Communication

Seth Polsley

3 PM Monday, June 5, 2017

Teague 326

Abstract

Between appointments, healthcare providers have limited interaction with their patients, but patients have similar patterns of care. Medications have common side effects; injuries have an expected healing time; etc. By modeling patient interventions with outcomes, healthcare systems can equip providers with better feedback. In this work, we present a pipeline for analyzing medical records according to an ontology directed at allowing closed-loop feedback between medical encounters. Working with medical data from multiple domains, we use a combination of data processing, machine learning, and clinical expertise to extract knowledge from patient records. While our current focus is on technique, the utlimate goal of this research is to inform development of a system using these models to provide knowledge-driven clinical decision-making.

Biography

Seth Polsley is a graduate student in the Department of Computer Science and Engineering at Texas A&M University and a research assistant in both the Sketch Recognition Lab and College of Medicine Biomedical Informatics Research group. Before joining A&M, he received a B.S. in Computer Engineering from the University of Kansas where he worked with the Speech and Applied Neuroscience Lab. His research interests may be broadly described as intelligent systems, which has led to work on multiple learning- based systems in the domains of education and health.

 

Advisor: Dr. Tracy Hammond

SRL MS Thesis Defense of Josh Cherian. Friday, December 9. Title: Recognition of Everyday Activities through Wearable Sensors and Machine Learning

Thesis Defense
Friday, December 9

Title: Recognition of Everyday Activities through Wearable Sensors and Machine Learning

Josh Cherian

10 AM Friday, December 9, 2016

Teague 326

Abstract
Over the past several years, the use of wearable devices has increased dramatically, largely due to their increasingly smaller and more personal form factors, greater sensor reliability, and increasing utility and affordability.  This has helped many people live healthier lives and achieve their personal fitness goals, as they are able to quantifiably and graphically see the results of their efforts every step of the way. While these systems work well within the fitness domain, they have yet to achieve a convincing level of functionality in the larger domain of healthcare.To facilitate the increased use of wearable devices to aid in healthcare, we present a two tier recognition system for identifying health activities in real time based on accelerometer data. To do this we run a series of users studies to collect data for six everyday activities: brushing one's teeth, combing one's hair, scratching one's chin, washing one's hands, taking medication, and drinking, achieving an f-measure of 0.85 when identifying these activities in a controlled setting. To evaluate our recognition system's ability to recognize activities in a naturalistic setting, we identify instances of brushing teeth over the course of a day. We initially achieve an f-measure of 0.68; however we are able to improve this to 0.85 by proposing and extracting several novel features. Through recognition of these activities, we aim to encourage the use of wearable devices for everyday personal health management. 

Biography
Josh Cherian is a MS candidate at Texas A&M University in the department of Electrical Engineering working under Dr. Tracy Hammond in the Sketch Recognition Lab. Josh completed his BS in Biomedical Engineering from Georgia Institute of Technology. His primary research interest is activity recognition, with a specific focus on recognizing daily health activities such as brushing one's teeth, washing one's hands, and taking medication.

Advisor: Dr. Tracy Hammond