Biomedical Informatics Commons^™

The Influence Of Mass Media On The Covid-19 Vaccination Decision-Making Process: A Prospective Survey-Based Study, Cameron Quon

Biomedical Sciences Publications

No abstract provided.

2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh

SDSU Data Science Symposium

Abstract. In this paper, we analyze deep visual features from 2D data representation(s) of the respiratory sound to detect evidence of lung abnormalities. The primary motivation behind this is that visual cues are more important in decision-making than raw data (lung sound). Early detection and prompt treatments are essential for any future possible respiratory disorders, and respiratory sound is proven to be one of the biomarkers. In contrast to state-of-the-art approaches, we aim at understanding/analyzing visual features using our Convolutional Neural Networks (CNN) tailored Deep Learning Models, where we consider all possible 2D data such as Spectrogram, Mel-frequency Cepstral Coefficients …

A Machine Learning Approach For Predicting Patient Mortality With Heart Rate Variability Statistics, Matthew Thiele, Dario Ghersi

Theses/Capstones/Creative Projects

The prediction of patient mortality in the healthcare system provides a metric by which hospitals can better manage patient care and assess the needs of each individual patient. As such, the development of better predictive methods is vital for improving patient outcomes and overall quality of care. Heart rate variability (HRV) is a measure of the heart’s complex beating patterns, giving medical professionals additional insight into patient health. Previous research has demonstrated the potential use of heart rate variability as a metric for patient mortality prediction for various conditions, however more work is necessary to validate HRV as a metric …

The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Mosaad Elsaid Mohamed Naglah

Electronic Theses and Dissertations

Computational technologies can contribute to the modeling and simulation of the biological environments and activities towards achieving better interpretations, analysis, and understanding. With the emergence of digital pathology, we can observe an increasing demand for more innovative, effective, and efficient computational models. Under the umbrella of artificial intelligence, deep learning mimics the brain’s way in learn complex relationships through data and experiences. In the field of bioimage analysis, models usually comprise discriminative approaches such as classification and segmentation tasks. In this thesis, we study how we can use generative AI models to improve bioimage analysis tasks using Generative Adversarial Networks …

Identifying And Minimizing Underspecification In Breast Cancer Subtyping, Jonathan Cheuk-Kiu Tang

Master's Theses

In the realm of biomedical technology, both accuracy and consistency are crucial to the development and deployment of these tools. While accuracy is easy to measure, consistency metrics are not so simple to measure, especially in the scope of biomedicine where prediction consistency can be difficult to achieve. Typically, biomedical datasets contain a significantly larger amount of features compared to the amount of samples, which goes against ordinary data mining practices. As a result, predictive models may fail to find valid pathways for prediction during training on such datasets. This concept is known as underspecification.

Underspecification has been more accepted …

Gene Therapy And Biomedical Applications, Sarah Dundore, Leena Pattarkine

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

Gene therapy has many uses today through the new treatment options and its potential to treat uncurable diseases. (Class Project)

Intracranial Convection-Enhanced Delivery Of Laponite Magnetic Iron-Oxide Nanoparticles- Faculty Research Symposium 2022, Kenneth Laihing Ph.D.

Student Posters

To make degradable nanofibers that can be used to make a bandage that releases antibiotics to fight infections for burn wounds.

Using Metabolic Potential Within The Airway Microbiome As Predictors Of Clinical State In Persons With Cystic Fibrosis, Gabriella Shumyatsky, Aszia Burrell, Hollis Chaney, Iman Sami, Anastassios C Koumbourlis, Robert J Freishtat, Keith A Crandall, Edith T Zemanick, Andrea Hahn

Department of Bioscience Technologies Faculty Papers

Introduction: Pulmonary exacerbations (PEx) in persons with cystic fibrosis (CF) are primarily related to acute or chronic inflammation associated with bacterial lung infections, which may be caused by several bacteria that activate similar bacterial genes and produce similar by-products. The goal of our study was to perform a stratified functional analysis of bacterial genes at three distinct time points in the treatment of a PEx in order to determine the role that specific airway microbiome community members may play within each clinical state (i.e., PEx, end of antibiotic treatment, and follow-up). Our secondary goal was to compare the change between …

Knowledge Network Embedding Of Transcriptomic Data From Spaceflown Mice Uncovers Signs And Symptoms Associated With Terrestrial Diseases, Amber M. Paul, Charlotte A. Nelson, Ana Uriarte Acuna, Ryan T. Scott, Atul J. Butte, Egle Cekanaviciute, Sergio E. Baranzini

Publications

There has long been an interest in understanding how the hazards from spaceflight may trigger or exacerbate human diseases. With the goal of advancing our knowledge on physiological changes during space travel, NASA GeneLab provides an open-source repository of multi-omics data from real and simulated spaceflight studies. Alone, this data enables identification of biological changes during spaceflight, but cannot infer how that may impact an astronaut at the phenotypic level. To bridge this gap, Scalable Precision Medicine Oriented Knowledge Engine (SPOKE), a heterogeneous knowledge graph connecting biological and clinical data from over 30 databases, was used in combination with GeneLab …

End-Organ Function And Exercise Performance In Patients With Fontan Circulation: What Characterizes The High Performers?, Scott J Weinreb, Kathryn M Dodds, Danielle S Burstein, Jing Huang, Elizabeth B Rand, Edna Mancilla, Jennifer R Heimall, Michael G Mcbride, Stephen M Paridon, David J Goldberg, Jack Rychik

Center for Advanced Practice

Background The physiologic hallmarks of the Fontan circulation-chronically elevated central venous pressures and low cardiac output-have significant effects not only on cardiovascular status but also impact other organ systems. Exercise capacity is limited in many and declines with age, accelerating in adolescence, but with wide variability. We explore the relationship between exercise performance and end-organ function in outpatient subjects with a Fontan circulation. Methods and Results This is a cross-sectional analysis of subject end-organ characterization from our outpatient Fontan circulation clinic with peak oxygen consumption (peak Vo