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Full-Text Articles in Medicine and Health Sciences

Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen Apr 2023

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 Apr 2023

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.


Medical Manikin Augmented Reality Simulation (M2ars), Pauline Delacruz, Jacob Gibson, Daniel Howard, Jaclyn Peacock, Kendall Robbins Apr 2022

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 Apr 2022

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 …


Iot Devices In The Public Health Sector, Cayla Young Jan 2020

Iot Devices In The Public Health Sector, Cayla Young

Cybersecurity Undergraduate Research Showcase

In this research, proper attention is drawn to privacy and security concerns with the integration of Internet of Things (IoT) devices in the public health sector. Often, not much attention is given to IoT devices and its vulnerabilities concerning the medical industry. Effects of COVID-19 contact tracing applications are explored through research of various source types. Mitigation techniques for these privacy and security issues is given. Focus is brought to topics outlining the risks associated with genetic testing companies and the vulnerabilities of data collection and data storage. Recommendations are provided to help consumers avoid these risks. Lastly, a comprehensive …