Preventive Care

Multi-epitope tick vaccines: From computational design to field deployment, immunoinformatics approaches, validation challenges, and translational pathways.

Ticks are major vectors of pathogens affecting both humans and animals, yet effective and sustainable control strategies remain limited. Conventional vaccines based on the concealed antigen Bm86 provide only partial protection and are often constrained by antigenic variability and strain-specific responses. Recent advances in immunoinformatics have enabled the rational design of multi-epitope vacc...

T-cell-mediated immunity to influenza A (H2N3): implications for caccine efficacy and cross-subtype protection.

Influenza A viruses pose a significant pandemic threat, with H2N3 in particular representing a subtype of particular concern due to limited population immunity and potential for zoonotic transmission. Traditional antibody-centric vaccine strategies face fundamental limitations stemming from antigenic drift and shift in hemagglutinin and neuraminidase surface proteins, necessitating annual reformul...

Enhancing Early Prediction of Gestational Diabetes Mellitus Through Data Augmentation and Feature Guidance: Model Development and Validation Study.

BACKGROUND: Early prediction of gestational diabetes mellitus (GDM) is critical for improving maternal health outcomes. However, predictive models are...

Artificial Intelligence-based predictive models for adverse blood donor reactions: a systematic review of immediate and delayed events and clinical data approaches.

BACKGROUND: A significant challenge in blood donation is the occurrence of adverse donor reactions (ADRs) and their subsequent negative impact on the ...

Clin-STAR Corner: Practice Changing Advances at the Interface of Artificial Intelligence/Machine Learning and Geriatrics.

Artificial intelligence (AI) methods, including machine learning (ML), are transforming healthcare by enabling personalized interventions that integra...

Development of an interpretable machine learning model for predicting stress urinary incontinence following the delivery of a first child.

INTRODUCTION: The goal of this research is to use machine learning (ML) techniques to create a risk prediction model for postpartum stress urinary inc...

Y-Polyp: research on devices for detecting colorectal polyps with limited samples.

BACKGROUNDS: Colonoscopy plays a crucial role in preventing the malignant transformation of colorectal polyps, with early diagnosis and detection of c...

The SUPREME Index for 30-day all-cause readmission: development and internal validation of a machine learning-based risk stratification index in community-dwelling adults.

BACKGROUND: Hospital readmissions are a key indicator of healthcare quality and have substantial implications for patient outcomes and system-level co...

The Evolution of Precision Anti-Doping From UGT2B17 Polymorphism Insights to Integrated Detection Frameworks.

Screening for endogenous anabolic-androgenic steroid abuse has long relied on the urinary testosterone/epitestosterone (T/E) ratio. However, this metr...

Evaluation of suicide behavior screening tools using machine learning and variable importance measures.

Suicide screening in military primary care settings is often conducted with a small number of self-report questions. The PRImary care Screening Method...

Uric Acid to HDL-C Ratio as a Novel Biomarker for Sarcopenia: A National Study with Machine Learning Insights.

BACKGROUND: Sarcopenia is a major age-related health burden. Although the uric acid to high-density lipoprotein cholesterol ratio (UHR) has been linke...

Using Machine Learning Methodology to Identify Predictors of Non-Response to MTSS-B: a Focus on Discipline Problems and Juvenile Justice Involvement.

Multi-tiered systems of support for behavior (MTSS-B) is a widely-used tiered preventive intervention currently used in over 25,000 schools across the...

Understanding Blood-Injection-Injury Phobia: Do Not Miss the Point.

Needle and blood-injection-injury phobia is commonly encountered in the perioperative setting. It can significantly disrupt operating room throughput,...

Lung Cancer Screening and Prevention: Beyond Conventional Strategies in a Rapidly Changing Global Milieu.

Lung cancer remains the leading cause of cancer-related mortality worldwide despite advances in early detection and treatment. Furthermore, its epidem...

Prediction of Early Functional Outcome After Acute Ischemic Stroke Using Real-World Clinical Data in Vietnam and Indonesia: Retrospective Cohort Study.

Accurate prediction of early functional outcome after acute ischemic stroke is critical for clinical decision-making. This retrospective cohort study ...

Predicting COVID-19 Vaccination Decision-Making Profiles Among Dutch Adults: From Survey to National Administrative Data.

Individual's vaccination behaviors are influenced by factors such as values and beliefs. Applying latent class analysis (LCA) to such factors from the...

The CT colonography radiology and data system: history, updates, and future directions.

Computed tomography colonography, also known as virtual colonoscopy, is a minimally invasive imaging technique developed in the early 1990s to evaluat...

Proximal Junctional Kyphosis Prevention in Adult Spinal Deformity Surgery: A Technical Review of Tethering and Adjunctive Strategies.

BACKGROUND AND OBJECTIVES: Proximal junctional kyphosis (PJK) and proximal junctional failure (PJF) remain significant complications after long-segmen...

ASO Special Article: Proceedings of the Inaugural Joint US-India Cancer Dialogue: Accelerating Collaboration to Advance Cancer Prevention, Early Detection, Treatment, and Care.

BACKGROUND: Cancer is a leading cause of death in both the USA and India. During Prime Minister Narendra Modi's State Visit to Washington, DC in June ...

End-user perspectives on the use of personal health information for AI development and the use of AI in care: an interview study.

INTRODUCTION: The rapid advancement of artificial intelligence (AI) in health care necessitates that decision-makers consider end-user views on second...