OBJECTIVE: To perform an external validation of a previously reported machine learning (ML) approach for predicting the diagnosis of pleural tuberculosis.
BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS) is common in adults while myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is rare. Our previous machine-learning algorithm, using clinical variables, ≤6 brain lesions, and no ...
Hospital readmissions prolong patient suffering and increase healthcare expenditures. While several studies have attempted to develop prediction models to reduce readmissions, most have demonstrated modest predictive accuracy. To improve upon prior a...
BACKGROUND: Fresh embryo transfer reduces waiting time and minimizes embryo cryodamage for endometriosis (EM) patients. The current prediction models for fresh embryo transfer outcomes in EM primarily rely on logistic regression, with limited applica...
INTRODUCTION: Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is crucial for implementing timely interventions. However...
BACKGROUND: The functioning of health care systems in emergencies relies on health care professionals (HCPs). During the COVID-19 pandemic, HCPs faced significant emotional challenges, which affected their productivity. Revealing HCPs' emotional resp...
OBJECTIVE: To test the applicability of deep learning models for detecting and staging rhegmatogenous retinal detachment (RRD) based on morphological features using two- and three-dimensional optical coherence tomography (OCT) scans.
INTRODUCTION: Cardiac magnetic resonance (CMR) is the gold standard for assessing left ventricular ejection fraction (LVEF). Artificial intelligence (AI)-based echocardiographic analysis is increasingly utilized in clinical practice.
Liver diseases, notably cirrhosis, pose a substantial global health challenge, resulting in millions of annual deaths. Existing diagnostic methods primarily target high-risk groups, leaving a significant portion of patients undiagnosed. This study ai...
PURPOSE: Pulmonary embolism (PE) is a significant cause of mortality in the United States. The objective of this study is to implement deep learning (DL) models using computed tomography pulmonary angiography (CTPA), clinical data, and PE Severity In...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.