Bioterrorism

Large Language Model Few-Shot Learning for Predicting Individual Treatment Response to Smartphone-Based Mindfulness in Autistic Adults With Anxiety: Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Anxiety disorders are highly prevalent among adults with autism, with 20%-65% experiencing at least one diagnosable anxiety disorder. While mindfulness-based interventions have demonstrated efficacy for anxiety reduction, treatment response varies considerably across individuals. Machine learning approaches offer potential for identifying who is most likely to benefit from smartphone-b...

Evolution of swine influenza surveillance and one health governance in Taiwan: from zoonotic risk management to integrated preparedness.

Influenza A viruses (IAVs) remain a persistent global threat because of rapid antigenic change, frequent genetic reassortment, and cross-species transmission. Swine act as key "mixing vessels," permitting co-infection with avian and human strains and accelerating viral diversification and zoonotic risk. Effective veterinary surveillance is therefore critical for detecting viral evolution within sw...

Multiscale Higher-Order Molecular Simplicial Complex Embedding for Drug Response Prediction.

MOTIVATION: Accurately predicting anticancer drug response is a central challenge in precision oncology. Existing computational methods, although valu...

Deep learning approaches for predicting response to neoadjuvant chemotherapy in muscle invasive bladder cancer: A systematic review.

Neoadjuvant chemotherapy (NAC) followed by radical cystectomy is the standard of care for muscle-invasive bladder cancer (MIBC), yet treatment respons...

Hybrid AI-Geo-informatics framework for river course change prediction and disaster risk mitigation.

Rivers are dynamic geomorphological systems that frequently alter their courses due to erosion, sediment deposition, channel migration, and flooding. ...

Optimizing Treatment Strategies in the Bipolar Disorder Spectrum With Classical AI Approaches: Systematic Review of Performance, Bias, and Clinical Applicability.

BACKGROUND: Bipolar disorder (BD) is a complex and heterogeneous psychiatric condition, characterized by fluctuating clinical courses that affect appr...

From Variant Interpretation to Biomarker Translation: Multi-omics Integration in Inherited Neuromuscular Diseases.

Genetic neuromuscular diseases are highly heterogeneous disorders characterized by diagnostic challenges and limited therapeutic options, underscoring...

A novel fever prevalence indicator for early warning of acute respiratory infections using wastewater-based epidemiology and machine learning.

The rapid spread of acute respiratory infections (ARIs) poses a major challenge to global public health, yet current surveillance systems relying on s...

Bridging the Vaccine Gap: Scientific and Technological Advances for Diseases Lacking Effective Vaccines.

Despite remarkable achievements in infectious disease control, more than 20 major pathogens responsible for significant global morbidity and mortality...

Investigating the relationship between attitudes toward artificial intelligence and moral sensitivity among nursing students.

INTRODUCTION: Given the increasing use of artificial intelligence in the field of health and treatment, including nursing, it is necessary to draw stu...

Clinical target volume radiomics from planning CT for pretreatment response prediction  in rectal cancer undergoing chemoradiotherapy.

PURPOSE: Response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer remains heterogeneous. This exploratory study evaluated whether radiomics f...

Development and multicenter validation of an AI-driven detection system for DLBCL cells in bone marrow smears.

The presence of diffuse large B-cell lymphoma (DLBCL) cells in bone marrow (BM) smears is recognised as a key morphological basis for diagnosing BM in...

The Role of Artificial Intelligence and Machine Learning in Predictive Virology: Forecasting, Tracking, and Combating Viral Threats.

The escalating threat of viral pandemics, dramatically illustrated by the COVID-19 crisis, has exposed the critical shortcomings of conventional react...

Quality, completeness, readability, and response time of AI chatbots in the management of deep caries and pulp exposure: a bilingual comparative study.

BACKGROUND: Artificial intelligence (AI) chatbots are being increasingly used to obtain health-related information; however, the quality, completeness...

Disease-modifying antirheumatic drugs (DMARDs) for rheumatoid arthritis after failure of biologic or targeted synthetic therapy: a systematic review and network meta-analysis.

RATIONALE: After inadequate response to first-line biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drug (DMARD) therapy in adult...

AI-Based Diagnostic Platform Capabilities With Lyme Disease as a Use Case: Integrative Exploration.

BACKGROUND: Lyme disease (LD) is the most common vector-borne disease in the United States. It is difficult to diagnose because it can mimic numerous ...

A Eu/Tb-Functionalized Hydrogen-Bonded Organic Framework for Ratiometric Sensing of Anthrax Biomarker and Integrated Intelligent Bactericidal Efficacy Evaluation.

Luminescent materials with stimulus-responsive and discriminable optical outputs are highly desirable for advanced on-site sensing and biosecurity mon...

Pharmacologic and expectancy effects in depression: Associations with inter-network resting-state connectivity.

Depression involves dysregulation across large-scale neural networks, yet substantial heterogeneity in resting-state functional connectivity (rsFC) ac...

Treatment-specific CT Radiomics Models To Predict Response To Neoadjuvant Therapy And Explore Individualized Treatment Selection In Gastric Cancer.

RATIONALE AND OBJECTIVES: To develop and compare general and treatment-specific radiomics models based on pretreatment computed tomography (CT) for pr...

Modelling climatic and temporal dynamics of dengue transmission in Bangladesh using deep learning models.

Dengue fever is a significant public health issue in tropical and subtropical areas, and predicting its spread is challenging due to the complex inter...