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Biomedical Informatics Commons™

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Full-Text Articles in Biomedical Informatics

Investigation Of The Utility Of A Ptsd Coaching Mobile App To Address Mental Health Services Demand In A Primary Care Clinic: Analysis Of Caps-5 Measures, Sindhura Nemani, Danielle Rae Schweitzer, Anne C. Jones May 2024

Investigation Of The Utility Of A Ptsd Coaching Mobile App To Address Mental Health Services Demand In A Primary Care Clinic: Analysis Of Caps-5 Measures, Sindhura Nemani, Danielle Rae Schweitzer, Anne C. Jones

Rowan-Virtua Research Day

The COVID-19 pandemic affected countless people globally, resulting in a greater need for mental health professionals and resources1. The demand for mental health care is soaring yet the limitation of resources has strained the healthcare system, making it challenging to help patients in a timely manner2. This poster represents a snapshot of a larger project that is striving to investigate an intervention to help bridge the gap between patient need and prompt referral through a warm handoff approach and use of the PTSD Coach mobile application as well as exploring patients’ satisfaction3,4,5,6,8,9. In this …


Unveiling The Potential: The Role Of Ai-Enhanced Ecg In Cardiovascular Disease Detection, Alisha Vincent May 2024

Unveiling The Potential: The Role Of Ai-Enhanced Ecg In Cardiovascular Disease Detection, Alisha Vincent

Rowan-Virtua Research Day

Background: The Electrocardiogram (ECG) is a widely utilized, non-invasive, cost-effective cardiac test. Its integration with Artificial Intelligence (AI) has empowered it to become a potent screening tool and a predictor for various cardiovascular diseases, especially in asymptomatic individuals. Objective: This review investigates the utility of AI-powered ECG in early detection of cardiac conditions, focusing on conditions such as low ejection fraction (LEF), atrial fibrillation (AF), aortic valve stenosis (AVS), and cardiac amyloidosis (CA). Methods: A literature review spanning 2018 to 2024 was conducted, analyzing 10 articles - 3 on AF, 3 on AVS, 3 on LEF, and …


Clinical Outcomes For Impella Patients Associated With Hyperlipidemia: An Analysis Of The National Inpatient Sample, Tony Elias, Sonika Vatsa, Kyrillos Girgis, Taha Syed, Rafail Beshai May 2024

Clinical Outcomes For Impella Patients Associated With Hyperlipidemia: An Analysis Of The National Inpatient Sample, Tony Elias, Sonika Vatsa, Kyrillos Girgis, Taha Syed, Rafail Beshai

Rowan-Virtua Research Day

The Impella, a ventricular assist device, is crucial for managing severe heart failure and cardiogenic shock. Despite its widespread use, there's scant information on how hyperlipidemia affects Impella patients. To address this gap, we delved into the National Inpatient Sample Database from 2019 and 2020. Our aim was to scrutinize in-hospital outcomes among these patients. We identified 8233 Impella patients, among whom 1012 (12.3%) had hyperlipidemia. Those with hyperlipidemia displayed higher rates of hypertension, diabetes mellitus, and chronic kidney disease compared to their counterparts without hyperlipidemia. Shockingly, in-hospital mortality was notably elevated in the hyperlipidemia group, emphasizing its clinical significance. …


Cardiovascular Disease Prediction Modelling: A Machine Learning Approach, Usmaan Al-Shehab, Maduka Gunasinghe, Yousuf Elkhoga, Nimay Patel, Juliana Yang May 2023

Cardiovascular Disease Prediction Modelling: A Machine Learning Approach, Usmaan Al-Shehab, Maduka Gunasinghe, Yousuf Elkhoga, Nimay Patel, Juliana Yang

Rowan-Virtua Research Day

The objective of this project is to utilize the UCI Heart Disease dataset to identify physiological biomarkers that are highly correlated with heart disease incidence. A predictive model can then be developed using these biomarkers to estimate the likelihood of someone having or developing a heart-related condition. This study compares the efficacy of predicting cardiovascular disease as an outcome using three machine learning algorithms: Support Vector Machine, Gaussian Naive Bayes, and logistic regression. Support Vector Machine works by creating hyperplanes between data points to conduct classification. Gaussian Naive Bayes works by using the conditional probabilities of events to classify the …