Bioterrorism

A Foundation Model Based CT Biomarker for Non-Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non-Small Cell Lung Cancer.

Predicting pathological complete response (pCR) to neoadjuvant immunochemotherapy in non-small cell lung cancer (NSCLC) is clinically important yet remains challenging. Here, we introduce a foundation model-derived computed tomography (CT) imaging biomarker established from a multi-center cohort of 702 patients. Specifically, we developed and validated a non-invasive baseline CT-based model for ri...

From Empirical Ratio Tuning to Mechanistic Insight: Decoding NiO-ZnO Heterojunction Effects in Gas Sensing via Explainable Machine Learning.

P-n heterostructures have been widely recognized as an effective strategy for enhancing the sensing performance of metal oxide semiconductor gas sensors. However, the regulatory mechanism underlying the NiO-ZnO composite ratio and its influence on gas sensing and recognition performance remains poorly understood. In this work, seven NiO-ZnO-based gas sensors with systematically varied molar ratios...

Readiness Assessment for AI in Nursing Care Projects: Multimethods Study.

BACKGROUND: Integrating artificial intelligence (AI) systems into nursing care often encounters obstacles stemming from unmet requirements and insuffi...

Occupational therapists' perceptions of artificial intelligence: Potential, preparedness, and training needs.

INTRODUCTION: Artificial intelligence (AI) is transforming health care, yet its impact on occupational therapy remains underexplored. This study inves...

Metabolomic Machine Learning Predictor for Adequate and Deep Response to UDCA in Non-Cirrhotic PBC.

BACKGROUND: Primary biliary cholangitis (PBC) patients exhibit heterogeneous responses to ursodeoxycholic acid (UDCA), with partial responders remaini...

Preparing Midwives for the Digital Future: A Qualitative Study on Academic Midwives' Perspectives on Artificial Intelligence in Education.

AIM: The aim of this study was to explore the perspectives of midwifery academics regarding the integration of Artificial Intelligence (AI) into midwi...

Neoadjuvant Immunotherapy in Locally Advanced Head and Neck Squamous Cell Carcinoma: From Oncologic Outcomes to Response-Adaptive Treatment De-escalation.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) are associated with poor 5-year survival and substantial treatment-related morbidity. Neoadj...

AI-driven big data analysis and predictive modeling of infectious disease immunity: from correlates to causal, multiscale understanding.

The ability to reliably predict protective immunity against infectious diseases remains a central challenge in immunology, vaccine development, and pu...

Innovative strategies for early detection of cardiotoxicity: artificial intelligence and multi-modality collaborative models.

Cancer therapeutics account for a significant proportion of new drug development, reflecting advances in diagnosis, treatment, and disease control. Ho...

AI-MIRACLE: Artificial Intelligence and MultIpaRAmetric MRI Predict CLinical OutcomEs to Neoadjuvant Immunotherapy in Patients with Muscle-invasive Bladder Cancer Undergoing Radical Cystectomy.

BACKGROUND AND OBJECTIVE: Neoadjuvant immune-checkpoint inhibitors (ICIs) in muscle-invasive bladder cancer (MIBC) were tested in patient's ineligible...

Improving the impact of medical student research through structured mentorship: a clinical research enterprise model.

PROBLEM: Medical student research engagement is increasingly important in residency selection and professional development, yet structured, longitudin...

KRASG12V/A146T mutations are associated with nCRT resistance via enhanced DNA double-strand break repair and support a deep learning prediction framework in LARC.

BACKGROUND: Neoadjuvant chemoradiotherapy (nCRT) is the standard treatment for locally advanced rectal cancer (LARC), yet clinically validated biomark...

Kinetic parameter prediction using neural networks identifies limitations to C4 photosynthesis.

Kinetic models of photosynthesis enable time-resolved predictions of traits related to this key process and provide the means to identify factors limi...

Deriving Clavien-Dindo Classification from Administrative Data: Development and External Validation in Hepatobiliary Surgery.

INTRODUCTION: Routine electronic health records (HER)/administrative data could enable time- and cost-efficient, real-time surveillance and health-eco...

Review of systemic therapy in HCC with an approach to response assessment in clinical practice.

Systemic therapy for hepatocellular carcinoma (HCC) has undergone rapid transformation over the past decade, significantly expanding treatment options...

Post-quantum cognitive zero trust architecture for healthcare IoT devices.

Healthcare IoT systems increasingly rely on interconnected, resource-constrained devices that are vulnerable to both classical and emerging quantum-en...

Development and validation of the Dental Artificial Intelligence Readiness and Acceptance Instrument (DAI-RAI) for dental professionals.

BACKGROUND: Artificial intelligence (AI), including applications such as radiographic image analysis, caries detection, and treatment planning, is inc...

Decision-Making Under Uncertainty in AI-Enabled Warfare: Implications for Education and Training.

In AI-enabled warfare, military medical officers may be required to make life-and-death decisions when artificial intelligence (AI) outputs are correc...

Predicting neoadjuvant breast cancer therapy response using BRIDGE from tumor transcriptomics and histopathology.

BACKGROUND: While expression-based signatures inform adjuvant therapy in breast cancer (BC), no approved molecular biomarkers exist for the neoadjuvan...

Beyond target lesions: Prognostic value of longitudinal AI-derived whole-body [1⁸F]FDG PET/CT metrics in metastatic melanoma.

PURPOSE: To investigate the prognostic value of an artificial intelligence (AI)-based semi-automated tool for longitudinal whole-body quantification o...