Bioterrorism

Screening for Periodontitis Using Blood Biomarkers and Demographic Data: A Machine Learning Study.

PURPOSE: Periodontitis is a common chronic disease associated with systemic conditions such as diabetes and cardiovascular disease. Diagnosis typically relies on dental examinations and radiographs, which may be underutilised by individuals who avoid, delay, or lack dental care. This study evaluated the potential of routine blood biomarkers and demographic data for screening moderate-to-severe per...

A translational multimodal machine-learning prototype predicting valproate response in epilepsy treatment.

OBJECTIVE: Epilepsy affects ~1% of the global population and often requires lifelong antiseizure medication (ASM) therapy. Valproic acid (VPA) is a commonly prescribed first-line ASM, yet only approximately half of patients achieve sustained seizure freedom. Treatment selection remains largely empirical. We aimed to develop and independently validate a multimodal predictive model to estimate respo...

Tumor-preserving Deformable Registration of Longitudinal Breast DCE MRI during Neoadjuvant Chemotherapy.

Purpose To develop a deep learning-based deformable registration method for breast dynamic contrast-enhanced (DCE) MRI that preserves tumor regions wh...

Deep learning for predicting patient drug response by transferring gene-level and cell-level knowledge to tumors.

Prediction of patient-level drug response is critical for precision oncology but remains limited by the scarcity of clinical data. While machine learn...

AI-guided integration of aging-related functional assessment to predict nonresponse to cardiac rehabilitation in heart failure.

BACKGROUND: Cardiac rehabilitation (CR) improves functional capacity and outcomes in patients with heart failure (HF). However, a clinically significa...

A real-time early warning system to anticipate respiratory disease outbreaks using transfer learning.

Respiratory disease outbreaks burden American healthcare systems with over one million hospitalizations annually, yet current surveillance systems lag...

Adaptive schedule deviation correction for complex information system projects: a graph neural network approach with knowledge distillation.

Schedule deviation continues to plague complex information system projects, with empirical surveys reporting that over 70% of such projects suffer mea...

The Role of Inflammatory Biomarkers in Disease Severity and Treatment Response across Psoriasis, Atopic Dermatitis, and Hidradenitis Suppurativa-A Narrative Review.

Chronic inflammatory skin diseases (CISDs) such as psoriasis (PsO), atopic dermatitis (AD), and hidradenitis suppurativa (HS) involve both cutaneous a...

Clinical outcomes and predictors of response to PD-(L)1 blockade in patients with NSCLC without actionable genomic alterations who never used tobacco.

PURPOSE: Predictive biomarkers of response to immune checkpoint inhibitors (ICI) remain poorly defined in patients with non-small cell lung cancer (NS...

Assessing community resilience during the first COVID-19 wave peak in a megacity in eastern China: a cross-sectional study using social media data.

OBJECTIVES: In the face of pandemics resulting from infectious disease, improving community resilience has become increasingly vital. China's sudden e...

Enhancing Drug Response Prediction in Epilepsy with Emerging Multimodal Models: Focus on Clinical, Pharmacologic, and Genomic Factors.

Epilepsy is a common neurological disorder, with approximately one-third of the affected population developing drug-resistant epilepsy despite the exp...

Crystal Facet Engineering-Photoexcitation-Machine Learning Synergy on Cu2O/CuO Heterojunctions for High-Performance Triethylamine Sensing.

Triethylamine (TEA), a typical biogenic amine indicative of protein spoilage and a common toxic chemical pollutant, requires highly sensitive detectio...

Measuring AI preparedness in health professions education: Evidence from a national survey of medical radiation science students and new graduates.

INTRODUCTION: Artificial intelligence (AI) in medical radiation science (MRS) is increasingly embedded in everyday clinical workflows. As AI systems a...

Predicting dynamic individual out-of-hospital cardiac arrest risks using explainable machine learning: a multicenter study in China.

Out-of-hospital cardiac arrest (OHCA) poses a significant public health challenge, with limited tools available for dynamic risk estimation under chan...

Concepts of RNA virus evolution for the design of better antiviral countermeasures.

This century, global human health has been marked by a seemingly increasing list of outbreaks and epidemics caused by RNA viruses - masters of rapid e...

Nursing Educators' Utility, Preparedness, and Attitudes Toward Generative Artificial Intelligence in Teaching and Assessment: A Scoping Review.

BACKGROUND: This scoping review examined literature on nursing educators' attitudes, preparedness, and utility of generative artificial intelligence (...

Comparative analysis of traditional and deep learning time series architectures for influenza A infectious disease forecasting.

Influenza A remains a major cause of respiratory mortality worldwide, motivating accurate forecasting to support timely preparedness and resource allo...

Identifying host-specific patterns in viral protein sequences to predict host spillover risk in animal and plant kingdoms.

Emerging pandemics are often driven by viral spillover events. However, predicting them remains difficult due to the complex interplay between viral g...

Geological and machine learning based landslide risk assessment in the context of community knowledge and perception.

Aizawl, located in Mizoram, northeast India, faces persistent landslide risk due to fragile geology, steep terrain, and unregulated urban expansion. T...

Enhancing Anatomy Learning Through Enhanced 3D Visualization: A Study on Student Perception and Engagement in Museum-Based Education.

Effective anatomy education is essential for medical training. While traditional anatomy instruction provides essential foundational knowledge, its ef...