Bioterrorism

Clustering of rheumatoid arthritis patients: an unsupervised machine learning approach for characterizing the TNFi response.

This study aimed to identifydistinct profiles of response to Tumor Necrosis Factor inhibitors (TNFi) in rheumatoid arthritis (RA) patients using unsupervised machine learning to integrate clinical, demographic, and genetic data. A cohort of 294 RA patients was analyzed using hierarchical clustering techniques. Data collected included body mass index (BMI), adherence to physical activity, prevalenc...

Knowledge and perception of artificial intelligence among operating room staff in educational hospitals: a cross-sectional survey.

BACKGROUND: Successful implementation of artificial intelligence (AI) in healthcare depends not only on technological performance but also on the readiness of healthcare professionals to understand, trust, and appropriately use AI-enabled systems. Evidence regarding AI knowledge among multidisciplinary operating room (OR) staff remains limited, particularly in low- and middle-income healthcare set...

Emerging and Re-Emerging Viral Infections in Poultry: Integrating Traditional and AI-Based Control Strategies.

Poultry production remains significantly challenged by emerging and re-emerging avian viral diseases, which are influenced by host-pathogen interactio...

Radiomics-Based AI for Predicting Neoadjuvant Immunochemotherapy Pathological Response in Non-Small Cell Lung Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide. Accurate early prediction of response ...

Surface-Enhanced Raman Spectroscopy for Viral Diagnostics: Principles, Strategies, Clinical Challenges, and Future Directions.

Viral outbreaks such as SARS-CoV, MERS-CoV, and COVID-19 underscore the urgent need for rapid, sensitive, and scalable diagnostic technologies. Curren...

Short-Term Efficacy of the Artificial Intelligence HeartBot II in Increasing Awareness and Knowledge of Heart Attack in Women: Protocol for a Randomized Controlled Trial With a Waitlist Control.

BACKGROUND: Heart disease remains a leading cause of death for women in the United States. Despite this burden, awareness that heart disease is the le...

Hydrogen-Based Long-Duration Energy Storage: Technologies, System Integration, and Techno-Economic Performance.

The escalating integration of variable renewable energy sources has underscored the need for scalable, long-duration energy storage (LDES) solutions t...

BID Artifacts: An Artificial Intelligence-powered Briefing-Intraoperative-Debriefing Platform for Competency-based Plastic Surgery Education.

BACKGROUND: The briefing-intraoperative-bebriefing (BID) framework has shown promise in surgical education but lacks scalable digital implementation. ...

Real-world analysis of depression-related adverse events associated with the adsorbed anthrax vaccine: integrating pharmacovigilance signals, machine learning risk prediction, and transcriptomic mechanisms.

BACKGROUND: Anthrax remains a life-threatening zoonotic disease in resource-limited settings. Adsorbed anthrax vaccine (AVA, BioThrax) is the only Uni...

Habitat-Based Radiomics Model of Pretreatment CT to Predict Pathological Response of Esophageal Squamous Cell Carcinoma to Neoadjuvant Chemoimmunotherapy: A Multicenter Prospective Study.

RATIONALE AND OBJECTIVES: Neoadjuvant chemoimmunotherapy (NCIT) has shown promising efficacy in locally advanced esophageal squamous cell carcinoma (L...

Explainable machine learning for spatial risk assessment of Hyphantria cunea (Lepidoptera: Erebidae) in China.

The fall webworm, Hyphantria cunea (Drury) (Lepidoptera: Erebidae), is a highly polyphagous invasive pest that poses increasing economic and ecologica...

Multi-modal ensemble learning prediction of anti-TNF treatment response in pediatric patients with Crohn's disease using clinical, radiomic, and deep learning MR enterography features.

BACKGROUND: Anti-tumor necrosis factor (TNF) medical therapy is a major advancement for Crohn's disease (CD) management, yet many patients fail to res...

Large Language Models as Health Information Tools: Patient Use and Trust in Otolaryngology.

OBJECTIVES: Patients increasingly use large language models (LLMs) for health information, yet their use patterns, perceptions, and impact on clinical...

AI-Based Spatiotemporal Analysis Reveals Distinct Neuronal Markers of Morphine Response during Chronic Pain in Mice.

Treatment of chronic pain often relies on long term use of analgesics, such as opioids like morphine. However, the habit-forming natures of such subst...

Prompt Framing and Evidence Requirement for AI-Generated Educational Responses in Dental Education: Experimental Study.

BACKGROUND: Large language models are increasingly used in health professions education; however, the role of prompt design in shaping their outputs r...

Practical applications of artificial intelligence in infectious disease surveillance and control: opportunities, challenges, and ethical considerations.

BACKGROUND: Artificial intelligence (AI) has been increasingly recognized as a public health tool with applications ranging from epidemiology, pandemi...

Radiomics Model Predicts Efficacy of First-Line CDK4/6 Inhibitor Combined with Endocrine Therapy in HR+/HER2- Advanced Breast Cancer.

INTRODUCTION: The combination of CDK4/6 inhibitors and endocrine therapy is the first-line standard regimen for advanced HR⁺/HER₂⁻ breast cancer. Howe...

Predictive Value of Endoscopy in the Identification of Complete Response After Neoadjuvant Therapy for Rectal Adenocarcinoma.

BACKGROUND: Large-scale evidence on the role of endoscopy alone as the assessment tool to identify complete response after neoadjuvant therapy in loca...

TSTScope Unifies Single-Cell Multi-Omics to Identify Functional T Cell States Predictive of Immunotherapy Response.

Immune checkpoint blockade (ICB) can produce durable responses in cancer, but reliable predictors of benefit are still lacking. CD8+ tumor-specific T ...

Use, Concerns, and Perspectives on AI in Health Care Among French Health Professionals and Students: Web-Based Cross-Sectional Survey.

BACKGROUND: AI is increasingly discussed and deployed in health care, yet safe and effective implementation depends on the preparedness, trust, and tr...