Bioterrorism

Structural imaging predictors of ketamine response in treatment-resistant depression: a machine learning approach.

Ketamine has demonstrated rapid antidepressant efficacy in treatment-resistant depression (TRD), but clinical decision-making is challenging due to variability in individual response. Current trial-and-error prescribing practices may expose patients to ineffective treatment and avoidable adverse effects, underscoring the need for reliable predictive tools to optimize treatment selection and suppor...

Intelligent water environment diagnosis and treatment center: A machine learning framework for automated surface water pollution management.

Surface water quality is essential for public health and ecosystem sustainability, but pollution events arise from distinct biogeochemical mechanisms that require differentiated responses. Conventional management systems nevertheless treat exceedance events as homogeneous emergencies, resulting in inefficient interventions and limited preparedness for true crises. Machine learning has improved wat...

Bridging innovation and implementation in laboratory medicine: insights from a global survey on unmet needs and emerging technologies.

Technological innovation in laboratory medicine is advancing rapidly, driven by artificial intelligence, next-generation sequencing, high-resolution m...

Drug Response Profile-Based Machine Learning Enables Strategic Cell Line and Compound Selection for Drug Development.

MOTIVATION: Early-stage drug discovery relies on testing compounds across a limited set of cell lines, making it challenging to capture biological div...

Machine learning-based integration of transcriptome and digital pathology for predicting chemoresistance in muscle-invasive bladder cancer.

Muscle-invasive bladder cancer (MIBC) presents with variable clinical and pathological features, leading to inconsistent responses to standard treatme...

Understanding Mortality Data: A Step-by-Step Guide to CDC WONDER, Joinpoint Analysis, and Forecasting Models.

BACKGROUND: The use of mortality data in public health research has surged with the rise of open-access databases such as CDC WONDER. However, caution...

Imaging and AI in tertiary prevention of lung cancer: Narrative review and clinical perspectives.

OBJECTIVE: To provide a structured narrative review of current evidence and future directions for artificial intelligence (AI) applications in the ter...

Ethical risk prevention in client generative artificial intelligence (genAI) use: Applying the primary risk-management model.

As clients increasingly use generative artificial intelligence for emotional support, psychologists now deal with unfamiliar ethical challenges that g...

An integrated AI-driven vaccine design process: a systematic review of workflows from generative design to translational prediction.

Traditional vaccine development faced significant hurdles, including lengthy timelines and high costs, which hindered rapid responses to pathogens. Al...

A comparison of two- and three-dose MVA-BN mpox vaccination series on anti-monkeypox virus immunity.

The 2022 global outbreak of clade IIb mpox represented a turning point in public health's handling of poxviruses. The primary vaccine available for th...

Leveraging large language models on free-text symptoms from participatory surveillance enhances pertussis forecasting in the United States.

BACKGROUND: Declines in childhood vaccination in the U.S. have contributed to a resurgence of vaccine-preventable diseases, including a notable increa...

Multiple machine learning models for the prediction of an early response to radioactive iodine therapy in hyperthyroidism: ablative dose concept.

BACKGROUND: The aim of this novel study was to explore the possibility of the development of a machine learning (ML) model that can predict early resp...

Enhancing precision nitrogen management in corn through integration of soil properties and remote sensing: A mechanistic approach.

Sustainable intensification of agriculture requires optimizing nitrogen (N) use efficiency while maintaining crop productivity. However, the complex i...

National Institute of Allergy and Infectious Diseases (NIAID) - Bundeswehr Institute of Radiobiology (BIR) Joint Programmatic Workshop on a Global Approach to Medical Countermeasure Development in Radiological Public Health Preparedness.

This invited commentary grew out of a presentation made at the 2025 ConRad Meeting in Munich, Germany, and summarizes talks made by researchers suppor...

Artificial Intelligence Models Using Magnetic Resonance Imaging to Predict Response to Chemoradiotherapy in Rectal Cancer: A Systematic Review.

BACKGROUND: Pathological complete response (pCR) following neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC) is a key prog...

Short-horizon PM2.5 forecasting from multi-station networks: a mask-aware, leakage-safe framework.

Accurate short-horizon forecasts of fine particulate matter (PM₂.₅) at station resolution are critical for advisories, clinical preparedness, and epis...

Multi-omics-based machine learning model predicts response and guides treatment in Crohn disease: a case study in nutritional therapy.

BACKGROUND: Biomarkers are needed to predict treatment response and guide therapeutic decisions in Crohn disease (CD). We aimed to develop and validat...

Toward an AI-integrated nursing curriculum: A Kano model analysis of generative AI competency needs.

BACKGROUND: Generative artificial intelligence (GenAI) is increasingly influencing nursing practice and education, yet a gap remains between technolog...

MRI-based interpretable deep learning radiomics for predicting treatment response in axial spondyloarthritis.

BACKGROUND: The clinical efficacy of tumor necrosis factor inhibitors (TNFi) in axial spondyloarthritis (axSpA) is limited by high non-response rates,...

Research priorities for improved pandemic and epidemic intelligence.

Pandemic and epidemic intelligence integrates surveillance data with contextual knowledge to assess health risks and inform public health decisions. A...