BACKGROUND: Predictive analytic models, including machine learning (ML) models, are increasingly integrated into electronic health record (EHR)-based decision support tools for clinicians. These models have …
A small fraction of frequent Emergency Department (ED) users contributes disproportionately to ED visits. Frequent ED users are at higher risk of poor healthcare outcomes. …
Introduction: We sought to identify the neural signatures of fluctuating symptoms in Parkinson’s Disease (PD) using a convolutional neural network (CNN) trained to classify motor …
Multimodal Spontaneous Emotion Database (MMSE) BP4D+ is a database with multimodal data from 140 subjects. Prior emotion recognition research has relied upon datasets with smaller, …
Introduction and Objective In pediatric medicine, the formal definition of sepsis continues to change. Timely recognition of sepsis and prompt antibiotic and fluid administration is …
Background: Sepsis is the leading cause of child death globally, with low- and middle-income countries (LMICs) bearing a disproportionate burden of deaths. LMICs often have …
Introduction: High-intensity focused ultrasound (HIFU) is a fully non-invasive means of tissue ablation which sends sonic energy through the body to heat a target. When …
Prediction of miscarriage and stillbirth remains a clinical challenge. Prior efforts to use machine learning tools have not used an ensemble weighted machine learning approach, …
Post-operative atrial fibrillation (POAF) is the most common complication after cardiac surgery and develops after approximately one-third of open cardiac surgical procedures. The implications for …
There is a need to improve both patients’ ability to identify warning signs of stroke and TIA and emergency department (ED) teams’ ability to diagnose …
Pulmonary Embolism (PE) poses significant health risks with rising mortality rates and complications like Chronic Thromboembolic Pulmonary Hypertension (CTEPH). This study aims to enhance risk …
This paper examines at common machine learning applications in the physical security environment which collect data and what that means in light of GDPR by …
Introduction: Pulmonary embolism (PE) is a significant cause of mortality in the United States. We aimed to develop deep learning models using computed tomographic pulmonary …
Stroke remains a prominent cause of morbidity and disability in our world today. Technologies such as computed tomography (CT) and magnetic resonance imaging (MRI) may …
Purpose: The prognosis and epidemiology of severe COVID-19 illness in patients with diabetic retinopathy (DR) are not well understood. Using electronic health record (EHR) data …
Tissue biopsy and the Gleason scale remain the standard care to predict the aggressiveness of prostate cancer. Recent studies have shown that other clinical factors …
