Bioterrorism

A novel bridge wind-induced vibration response prediction algorithm based on temporal convolution network.

The stiffness of the high pier, large span rigid bridge in the operation period increases its ability to resist wind-induced vibration. However, the structural properties of high piers and long cantilevers make it susceptible to wind-induced vibration during construction in solid wind areas, which brings safety risks. The wind vibration response has strong nonlinear and random fluctuation characte...

AIxBio: Opportunities to Strengthen Health Security.

Artificial Intelligence (AI) has the potential to revolutionize biosecurity, health security, biodefense, and pandemic preparedness by offering groundbreaking solutions for managing biological threats. This landscape review explores recent advancements in AI across these fields, drawing from both grey literature and peer-reviewed studies published between January 2019 and February 2024. AI has dem...

A dynamical anthrax toxin nanopore biosensor for high-fidelity single-peptide classification.

Nanopore sensing holds the potential to revolutionize proteomics, yet current methods often rely on ensemble aggregation, where thousands of events mu...

Lesion-level dual-tracer PET biomarkers predict prognosis in multiple myeloma treated with CXCR4-directed radiopharmaceutical therapy.

BACKGROUND: C-X-C motif chemokine receptor 4 (CXCR4)-directed radiopharmaceutical therapy (RPT) represents a promising option for hematologic malignan...

In Situ Evaluation of Virtual Reality Simulation Usability and Learning in Nursing.

BACKGROUND: Virtual reality is increasingly applied in nursing education to enhance student readiness for patient care. This study evaluated the effec...

Intelligent fire detection in agriculture using machine learning and embedded systems for risk prevention and improved sustainability.

This research proposes the design of an autonomous fire detection system based on a Raspberry Pi 3 B+, combined with smoke and flame sensors, enabling...

Machine learning models classifiers enable a strong prediction of radioembolization-induced liver disease, and define a new bilirubin threshold for selection of patients.

PURPOSE: Selective Internal Radiotherapy (SIRT) is an established treatment option for hepatocellular carcinoma (HCC). However, a major complication i...

Young academic psychiatrists in 2050s: future directions across low- and high-income settings.

Academic psychiatrists inhabit two professional identities: clinician and researcher. In some settings they also carry out teaching to a range of staf...

Emerging Roles of Multiparametric Biodosimetry and Artificial Intelligence in Advancing Radiation Dose Assessment for Triage.

Biodosimetry plays a crucial role in radiation emergency preparedness and response by enabling efficient allocation of medical resources through prior...

Leveraging Machine Learning to Uncover Ethnic-Specific Predictors of Maternal Postpartum Depression.

Maternal postpartum depression (PPD) is a significant mental health issue that affects over 15% of mothers, with adverse effects on their children. Et...

Utilisation of intramuscular and intermuscular fat to develop a new skeletal muscle grading score which can predict treatment outcomes for locally advanced rectal cancer.

BACKGROUND: Sarcopenia has been widely studied in rectal cancer with increasing evidence to suggest that other body composition parameters, in particu...

Leveraging probabilistic forecasts for dengue preparedness and control: The 2024 Dengue Forecasting Sprint in Brazil.

Forecast models are a key decision-support tool for public health authorities in managing epidemics, feeding into early warning systems, scenario eval...

Responsible AI in Canadian Healthcare: Evaluation Frameworks, Challenges, and Policy Directions.

Artificial intelligence (AI) is transforming healthcare through advances in imaging, predictive analytics, and workflow optimization. However, its ado...

Open-set deep learning enabled LIBS sensor for label-free and on-site identification of unknown pathogen powders.

On-site and label-free identification of pathogen powders is critical for effective biosecurity and bioterrorism response. Laser-Induced Breakdown Spe...

Can Artificial Intelligence Be Used to Predict Response in Rectal Cancer? Current Evidence and Future Possibilities.

Artificial intelligence (AI) offers a promising solution to the long-standing challenge of accurately predicting treatment response in rectal cancer. ...

Re-envisioning the North American Biodosimetry Assessment Networking Group.

The RNCP/NIAID recommends the creation of a North American Biodosimetry Assessment Networking Group (BANG) by developing a blueprint for integrating t...

Multi-model large-scale AI framework for avian influenza surveillance and preparedness: Harnessing large language models to enhance risk communication, real-time decision support, and public health response strategies.

Avian influenza remains a persistent threat to global health security, with serious consequences for food systems, trade, and pandemic preparedness. T...

NIAID Biodosimetry Strategic Plan.

In the face of emerging threats from natural disasters, nuclear accidents, and potential malicious use of radiation, the National Institute of Allergy...

Predictors of Glycemic Response to Sulfonylurea Therapy in Type 2 Diabetes Over 12 Months: Comparative Analysis of Linear Regression and Machine Learning Models.

BACKGROUND: Sulfonylureas are commonly prescribed for managing type 2 diabetes, yet treatment responses vary significantly among individuals. Although...

Creation of the Sonntag Virtual Reality Laboratory: A Framework for Innovation in Neurosurgical Training and Global Education.

BACKGROUND AND OBJECTIVES: Neurosurgical education requires innovative approaches to meet the demands of an evolving field and adequately train the ne...