Bioterrorism

Physics-informed deep learning for rapid marine radionuclide dispersion forecasting in nuclear emergency response.

In the event of a severe nuclear accident at a coastal nuclear power plant, the rapid and accurate assessment of radionuclide dispersion in surrounding coastal waters is critical for effective emergency response. To overcome the inherent latency and predictive fidelity limitations of conventional marine dispersion simulations, this study develops an innovative hybrid Physics-Informed Deep Learning...

Enhancing flood prediction through physics-driven typhoon feature engineering and machine learning.

Typhoon-induced extreme floods pose severe threats to subtropical watersheds, yet systematic integration of typhoon physics into machine learning flood prediction remains limited. This study developed a physics-informed machine learning framework for the Boluo watershed, South China, emphasizing typhoon feature engineering. Four models (Linear Regression (LR), Artificial Neural Network (ANN), Rand...

Circulating Neutrophils Exhibit an Altered Immune Response in Chronic LUTS: An Image-Based Deep Learning Analysis.

INTRODUCTION AND HYPOTHESIS: Chronic lower urinary tract symptoms (LUTS) are characterised by persistent symptoms and elevated urinary leukocyte count...

Spatial proteomics of tertiary lymphoid structures reveals correlation with immunotherapy response in Merkel cell carcinoma.

BACKGROUND: Tertiary lymphoid structures (TLS) are ectopic lymphoid formations within or around tumours. They are emerging as important predictors of ...

EAC-Agent: A deep learning framework for multimodal emotion-aware conversational agent with contextual response generation.

Conversational agents, commonly referred to as chatbots, have become an integral part of various important applications, such as customer support and ...

Artificial intelligence in hepatocellular carcinoma: imaging-based subtyping and prediction of treatment response and prognosis.

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, accounting for nearly 90% of primary liver cancers worldwide. It is a biol...

Artificial intelligence literacy, readiness, and innovativeness: Exploring interrelationships in undergraduate nursing students.

AIM/OBJECTIVE: This study aimed to examine the relationships between AI literacy, medical AI readiness, and individual innovativeness among nursing st...

Emotion Expression in Breast Cancer Support Seeking: Empirical Study of an Online Community.

BACKGROUND: Breast cancer affects millions of women and presents not only medical challenges but also emotional, financial, and social burdens. Beyond...

Integrated genomic profiling identifies predictive biomarkers for neoadjuvant therapy response in Chinese breast cancer patients.

Neoadjuvant therapy (NAT) has emerged as a standard treatment strategy for locally advanced breast cancer (BC), yet robust biomarkers for response pre...

Content analysis of output from generative artificial intelligence chatbots when prompted about breast cancer and alcohol consumption.

OBJECTIVES: Alcohol is a group one carcinogen and contributes to breast cancer risk for women. Awareness of this relationship remains low. Generative ...

Artificial intelligence at the frontlines: Emerging infectious and parasitic diseases in the digital era.

Emerging infectious diseases are one of the most significant threats to global health, driven by many factors such as zoonotic spillovers, climate cha...

Quantitative CT Perfusion as a prognostic biomarker for chemotherapy response in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: Response evaluation of pancreatic ductal adenocarcinoma (PDAC) with routine contrast-enhanced CT (CECT) using RECIST is currently inadequa...

Identifying treatment response classes to transcranial direct current stimulation (tDCS) from daily ecological momentary assessment (EMA) patterns in patients with depression.

IMPORTANCE: Transcranial direct current stimulation (tDCS) is known to be promising for depression, but heterogeneity across studies highlights the ne...

Impact of a personalized antidepressant prescription using genetics, socio-demographic and clinical data in major depressive disorder patients: A clinical study.

BACKGROUND: Major depressive disorder (MDD) is common and disabling, and antidepressant selection often follows a trial-and-error process. Predictix i...

Mpox Awareness and Knowledge Among Residents of the Northern Border Region, Saudi Arabia: Implications for Community Preparedness.

In August 2024, the World Health Organization declared the ongoing mpox upsurge in Africa a Public Health Emergency of International Concern, undersco...

Predictive neuroimaging biomarkers of major depressive disorder treatment response: An umbrella review.

Major depressive disorder (MDD) is a heterogeneous condition with varied responses to pharmacological, psychotherapeutic, and neuromodulation interven...

Assessing plague risk across seven decades of environmental change in Inner Mongolia, China: An interpretable machine learning.

Plague, caused by Yersinia pestis, persists as a public health threat, particularly in natural foci such as China's Inner Mongolia Autonomous Region. ...

Beyond literacy to clinical competency: A framework for integrating generative AI into nursing education.

PROBLEM: Health systems are rapidly integrating generative artificial intelligence (GenAI) into clinical workflows, introducing safety risks including...

Exploring novel kinetics of automated H2O2 nebulization: a breakthrough in SARS-CoV-2 elimination.

Although hydrogen peroxide (H2O2) nebulization has shown promise for reducing SARS-CoV-2 loads in healthcare settings, its precise kinetics and real-w...

Integrated bioinformatics reveals tubulointerstitial immune microenvironment signatures and machine learning-driven prognostication of clinical treatment response in lupus nephritis.

Lupus nephritis (LN) represents the most severe renal manifestation of systemic lupus erythematosus (SLE), contributing to significant morbidity. Whil...