BACKGROUND: There is a lack of atrial fibrillation (AF) prediction models tailored for individuals without prior cardiovascular diseases (CVDs) to facilitate early intervention. This study aimed to develop and validate an AF prediction model using ma...
INTRODUCTION: This study seeks to determine incidence, comorbidities and drivers for new HIV infections to develop, test and validate a risk prediction model for screening for new cases of HIV.
OBJECTIVES: The objective of this study was to identify risk factors for enema reduction failure and to establish a combined model that integrates deep learning (DL) features and clinical features for predicting surgical intervention in intussuscepti...
BACKGROUND: In hospitals, Code Blue is an emergency that refers to a patient requiring immediate resuscitation. Over 85% of patients with cardiopulmonary arrest exhibit abnormal vital sign trends prior to the event. Continuous monitoring and accurate...
BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic disease characterized by a broad spectrum of involved organs, including neurological, renal, and vascular domains, with disease activity manifesting through unpredictable patterns that vary ...
BACKGROUND AND OBJECTIVES: Accurate interpretation of electrodiagnostic (EDX) studies is essential for the diagnosis and management of neuromuscular disorders. Artificial intelligence (AI) based tools may improve consistency and quality of EDX report...
BACKGROUND: Social media platforms offer valuable insights into patients' experience, revealing organic conversations that reflect their immediate concerns and needs. Through active listening to lived experiences, we can identify unmet needs and disc...
This mixed-methods study investigated the impact of AI-powered assistive technology on mobility, communication, and daily living assistance in children with Down syndrome in Saudi Arabia. We looked at information from 123 carers (47 who used AI and 7...
OBJECTIVE: To predict the actual number of COVID-19 cases in Brazilian pregnant and postpartum women diagnosed with Severe Acute Respiratory Syndrome using a predictive model created based on data from Brazilian database.
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