Academic Articles & Research Papers

Admission cardiac and renal biomarkers for early identification of type 1 cardiorenal syndrome after acute myocardial infarction.

Fear of Falling After Total Knee Replacement: A Saudi Experience

Background: Fear of falling (FOF) is a significant concern among older adults, especially after total knee arthroplasty (TKA). FOF can limit daily activities, reduce quality of life, and hinder recovery. This study aimed to investigate the ...

Artificial intelligence for pediatric height prediction using large-scale longitudinal body composition data

Objective We developed a precise, reliable artificial intelligence (AI) model for predicting the future height of children and adolescents based on anthropometric and body composition data. Materials and Methods We used an extensive longitu...

Open Posterolateral Elbow Dislocation in an Adult after Low-Energy Trauma: A Case Report Highlighting Diagnostic and Operative Considerations

Introduction: Open elbow dislocations are rare injuries in adults, accounting for ...

Deployment-related mental health support: comparative analysis of NATO and allied ISAF partners

Background: For years there has been a tremendous gap in our understanding of the mental health effects of deployment and the efforts by military forces at trying to minimize or mitigate these. Many military forces have recently systematize...

Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer

Gastrointestinal cancers (GICs) remain the most diagnosed cancers and accounted for the highest cancer-related death globally. The prognosis and treatment outcomes of many GICs are poor because most of the cases are diagnosed in advanced me...

Machine learning framework for early identification of high-spending Crohn’s disease patients using administrative claims

Objectives To develop and evaluate a machine learning (ML) model that predicts Crohn’s disease (CD) patients responsible for the top quartile of healthcare spending.Methods De-identified commercial claims (2016–2018) from ~267 000 continuou...

Development and validation of an interpretable machine learning model for predicting the risk of coronary heart disease risk in diabetes mellitus patients: a dual-center retrospective study

Abstract Background Diabetes mellitus (DM) combined with coronary heart disease (CHD) significantly increases the risk of cardiovascular events with a greater mortality rate. Therefore, establishing a predictive model can help DM patients r...

Dynamic monitoring of circulating tumor DNA reveals outcomes and genomic alterations in patients with relapsed or refractory large B-cell lymphoma undergoing CAR T-cell therapy

Background Over 50% of patients with relapsed or refractory large B-cell lymphoma (r/r LBCL) receiving CD19-targeted chimeric antigen receptor (CAR19) T-cell therapy fail to achieve durable remission. Early identification of relapse or prog...

Impact of preoperative insomnia on poor postoperative pain control after elective spine surgery and the modified Calgary postoperative pain after spine surgery (MCAPPS) score

Background: Approximately 30% to 64% of patients experience inadequate pain control following spine surgery. The Calgary postoperative pain after spine surgery (CAPPS) score was developed to identify this subset of patients. The impact of p...

SAM-trace: a fuzzy logic approach in identifying interaction effects in the exacerbation of childhood malnutrition severity

Abstract Pediatric malnutrition remains a major global health challenge. Conventional WHO-based binary classification (Severe Acute Malnutrition (SAM) / Moderate Acute Malnutrition (MAM) relies solely on anthropometric thresholds. It fails ...

Analysis of Customer Churn Classification for Sinarmas Syariah Lhokseumawe Insurance Services Using Deep Learning Tabnet and Explainable AI

Customer churn is a major challenge in the insurance industry because it directly affects customer retention, business sustainability, and company profitability. Early identification of customers at risk of churn is therefore essential for ...

Artificial Intelligence and Acute Stroke Imaging

Artificial intelligence technology is a rapidly expanding field with many applications in acute stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute stroke is critical for initiating prompt intervention ...

Math Anxiety, Working Memory, and Math Achievement in Early Elementary School

Although math anxiety is associated with poor mathematical knowledge and low course grades (Ashcraft & Krause, Citation2007), research establishing a connection between math anxiety and math achievement has generally been conducted with you...