Medicine and Health Sciences Commons^™

Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen

Modeling, Simulation and Visualization Student Capstone Conference

Protein modeling is a rapidly expanding field with valuable applications in the pharmaceutical industry. Accurate protein structure prediction facilitates drug design, as extensive knowledge about the atomic structure of a given protein enables scientists to target that protein in the human body. However, protein structure identification in certain types of protein images remains challenging, with medium resolution cryogenic electron microscopy (cryo-EM) protein density maps particularly difficult to analyze. Recent advancements in computational methods, namely deep learning, have improved protein modeling. To maximize its accuracy, a deep learning model requires copious amounts of up-to-date training data.

This project explores DeepSSETracer, a …

A Comparison Of Nonverbal And Paraverbal Behaviors In Simulated And Virtual Patient Encounters, Sarah Powers, Mark W. Scerbo, Matthew Pacailler, Macy Kisiel, Baillie Hirst, Ginger S. Watson, Lauren Hamel, Fred Kron

Modeling, Simulation and Visualization Student Capstone Conference

The present study assessed whether trainees display similar nonverbal and paraverbal behaviors when interacting with a simulated (SP) and virtual patient (VP). Sixty second slices of time following four interactions were rated for the presence and frequency of three nonverbal and paraverbal behaviors. Results revealed that students exhibited fewer behaviors in the VP interaction, possibly due to differences social inhibition or fidelity between the two formats.

Review Of Nighttime Temperature Effects On Long-Term Health Condition Through Sleep Studies, Sydnie Matkins

Modeling, Simulation and Visualization Student Capstone Conference

Over the past 40 years, there has been increasing interest in human sleep quality and duration. This nonsystematic review looked at over 80 peer-reviewed papers on the association among sleep, temperature, and long-term health conditions. Generally, warmer temperatures lend to poorer sleep quality, and poor sleep quality lend to mental illness and a higher risk of coronary heart disease and mortality. Future research should be to conduct a study that relies more on health records rather than questionnaires to accurately map current and future health quality.

Medical Manikin Augmented Reality Simulation (M2ars), Pauline Delacruz, Jacob Gibson, Daniel Howard, Jaclyn Peacock, Kendall Robbins

Modeling, Simulation and Visualization Student Capstone Conference

The Medical Manikin Augmented Reality Simulation (M2ARS) is an augmented reality simulation application built for the Microsoft HoloLens 2 that uses the principles of anatomy transfer to overlay human anatomical structures onto a medical manikin digitally. These structures currently consist of the skeletal, muscular, and circulatory systems. In addition, a model of the lungs and an animated heart are also available within the simulation. M2ARS allows the user to view these structures in a manner that is both visually and spatially accurate to the human body. This application contains two modes; an augmented reality mode, which uses a manikin, and …

Multi-Modality Breast Mri Segmentation Using Nn-Unet For Preoperative Planning Of Robotic Surgery Navigation, Motaz Alqaoud, John Plemmons Md, Eric Feliberti Md, Facs, Krishnanand Kaipa, Siqin Dong, Gabor Fichtinger, Yimming Xiao, Michel Audette

Modeling, Simulation and Visualization Student Capstone Conference

Segmentation of the chest region and breast tissues is essential for surgery planning and navigation. This paper proposes the foundation for preoperative segmentation based on two cascaded architectures of deep neural networks (DNN) based on the state-of-the-art nnU-Net. Additionally, this study introduces a polyvinyl alcohol cryogel (PVA-C) breast phantom based on the segmentation of the DNN automated approach, enabling the experiments of navigation system for robotic breast surgery. Multi-modality breast MRI datasets of T2W and STIR images were acquired from 10 patients. Segmentation evaluation utilized the Dice Similarity Coefficient (DSC), segmentation accuracy, sensitivity, and specificity. First, a single class labeling …