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Machine learning enhanced expert system for detecting heart failure decompensation using patient reported vitals and electronic health records.
Scientific reports
Aug 22, 2025
Heart failure (HF) is a condition with periods of stability interrupted by periods of worsening symptoms, known as decompensation episodes. Digital interventions are promising tools to alleviate burdens on HF management through automated alerts at th...
Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study.
Translational psychiatry
Aug 22, 2025
Previous studies have found that major depressive disorder (MDD) may accelerate overall structural brain aging. Nevertheless, it still remains unknown whether anhedonia, a critical negative prognostic indicator in MDD, further leads to advanced brain...
Machine-learning approach to atrial fibrillation prediction among individuals without prior cardiovascular diseases.
Open heart
Aug 22, 2025
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...
Development and validation of a predictive model for new HIV infection screening among persons 15 years and above in primary healthcare settings in Kenya: a study protocol.
BMJ health & care informatics
Aug 22, 2025
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.
Predictive model integrating deep learning and clinical features based on ultrasound imaging data for surgical intervention in intussusception in children younger than 8 months.
BMJ open
Aug 22, 2025
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...
Deep Learning-Based Early Warning Systems in Hospitalized Patients at Risk of Code Blue Events and Length of Stay: Retrospective Real-World Implementation Study.
JMIR medical informatics
Aug 22, 2025
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...
Prediction of 1-Year Activity in Systemic Lupus Erythematosus: Hierarchical Machine Learning Approach.
JMIR formative research
Aug 22, 2025
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 ...
AI-Based EMG Reporting: A Randomized Controlled Trial.
Journal of neurology
Aug 22, 2025
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...
Social Media Insights Into Disease Burden in Patients and Caregivers of Myelodysplastic Syndrome: Subcohort Analysis of High-Risk Patients.
Journal of medical Internet research
Aug 22, 2025
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...
Assessing the impact of AI tools on mobility and daily assistance for children with down syndrome in Saudi Arabia.
Scientific reports
Aug 22, 2025
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...
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