Date of Award

January 2019

Document Type

Open Access Thesis

Degree Name

Medical Doctor (MD)

Department

Medicine

First Advisor

Richard A. Taylor

Abstract

The intent of this thesis was to develop several medically applied artificial intel-ligence programs, which can be considered either clinical decision support tools or pro-grams which make the development of such tools more feasible. The first two projectsare more basic or "bench" in focus, while the final project is more translational. The firstprogram involves the creation of a residual neural network to automatically detect thepresence of pericardial effusions in point-of-care echocardiography and currently hasan accuracy of 71%. The second program involves the development of a sub-type ofgenerative adverserial network to create synthetic x-rays of fractures for several pur-poses including data augmentation for the training of a neural network to automat-ically detect fractures. We have already generated high quality synthetic x-rays. Weare currently using structural similarity index measurements and Visual Turing testswith three radiologists in order to further evaluate image quality. The final projectinvolves the development of neural networks for audio and visual analysis of 30 sec-onds of video to diagnose and monitor treatment of depression. Our current root meansquare error (RMSE) is 9.53 for video analysis and 11.6 for audio analysis, which arecurrently second best in the literature and still improving. Clinical pilot studies for thisfinal project are underway. The gathered clinical data will be first-in-class and ordersof magnitude greater than other related datasets and should allow our accuracy to bebest in the literature. We are currently applying for a translational NIH grant based onthis work.

Comments

This is an Open Access Thesis.

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