Bioterrorism

Machine Learning Models for Predicting Response to Percutaneous Transhepatic Biliary Drainage in Malignant Obstructive Jaundice: A Retrospective Cohort Study.

BACKGROUND AND AIMS: Percutaneous transhepatic biliary drainage (PTBD) is a standard palliative intervention for malignant obstructive jaundice, yet 60-75% of patients fail to achieve a clinically meaningful biochemical response. Pre-procedural identification of responders has direct implications for patient selection and shared decision-making. We developed and validated machine learning (ML) mod...

Alignment Between Large Language Models and Consensus in Endoscopic Spinal Disc Surgery: A Comparative Analysis Against the Neurocore-SENSED.

BACKGROUND: The Neurocore-SENSED framework, derived from a three-round modified Delphi process involving 77 international spine surgeons, provides a structured reference standard for reporting in endoscopic spine surgery (ESS) for disc disease. The ability of large language models (LLMs) to reproduce graded levels of expert agreement within a reporting framework has not been examined in ESS. OBJEC...

Adaptive NLI-Driven Claim Verification with Statistical Decision Modeling for Low-Latency Hallucination Reduction in Large Language Models.

Large Language Models (LLMs) exhibit a critical tendency to generate factually incorrect yet linguistically fluent outputs - a phenomenon termed hallu...

Oral and gut microbiota profiles in patients with locally advanced rectal cancer with varying responses to neoadjuvant chemoradiotherapy.

Recent research has focused on gut bacteria in colorectal cancer, but the influence of other microbiota, including oral and nonbacterial gut microbiot...

Medicines, misinformation and machines: Navigating infodemics in the generative AI era.

Health information is now widely accessed through smartphones, online searches and increasingly through generative artificial intelligence (AI). These...

Validity and Reliability of the Medical Artificial Intelligence Readiness Scale, Korean Version: A Methodological and Cross-Sectional Study.

This study aimed to translate and culturally adapt the Medical Artificial Intelligence Readiness Scale for Medical Students into Korean and to examine...

Bridging Machine Learning and Event-Based Analyses to Assess Maternal Contingent Responses to Infant Nondistress and Distress Vocalizations From Home Audio Recordings.

Caregiver-infant vocal interactions are foundational for early development, yet most evidence is derived from brief laboratory or home-visit observati...

Integrated pan-cancer analysis reveals a cancer-associated fibroblast oxidative stress response signature predicting immunotherapy response and prognosis.

Oxidative stress plays a significant regulatory role in tumor immune responses and can influence the efficacy of immunotherapy. Accordingly, therapeut...

Machine learning-driven drug repurposing and computational validation for Nipah virus.

The recurring Nipah virus outbreaks and the lack of effective antiviral therapies, emphasize the urgent need for effective therapeutic interventions. ...

When Deepfakes Meet Herd Immunity: Artificial Intelligence, Vaccine Avoidance, and the Next Infodemic Threat.

Vaccination remains among the most effective public health interventions, but its impact increasingly depends on public trust and a reliable informati...

Clinician-led, AI-assisted clinical software development: multi-domain verification of a deployed ePROM application.

BACKGROUND: Generative AI lowers the technical barrier to clinician-led software development, but functional success and usability do not establish cl...

The Future of Healthcare Leadership Education: A Consensus Vision and Research Agenda from an International Working Group.

Healthcare systems worldwide face escalating complexity driven by workforce shortages, increasing patient acuity, interprofessional practice demands, ...

Artificial intelligence responses to toilet training questions: A reliability and readability analysis of ChatGPT and gemini applications.

BackgroundToilet training is a critical developmental milestone that may have long-term implications for children's psychosocial development if improp...

Radiologic, Pathologic, and Deep Learning Predictors of Response to Immune Checkpoint Blockade in Renal Cell Carcinoma Patients Undergoing Post-Treatment Nephrectomy.

Response assessment of primary kidney tumors in the consolidation cytoreductive and neoadjuvant settings offers a unique opportunity to inform postope...

AI-derived Histopathological Signatures Are Associated With Response to Mepolizumab in Chronic Rhinosinusitis With Nasal Polyps.

BackgroundChronic rhinosinusitis with nasal polyps (CRSwNP) is a heterogeneous inflammatory disease with variable response to biologic therapy. Tissue...

Perceptions, knowledge and adoption of artificial intelligence in rheumatology: results from a British Society for Rheumatology survey.

OBJECTIVES: Artificial intelligence (AI) and machine learning applications are rapidly expanding across healthcare. Successful implementation of AI te...

[Reflections on surgical management strategies for locally advanced gastric cancer after neoadjuvant immunotherapy].

Neoadjuvant immunotherapy is reshaping the treatment landscape of locally advanced gastric cancer (GC). The central clinical challenge has expanded fr...

Artificial intelligence-driven prediction of neoadjuvant chemotherapy response in adult patients with gastric cancer: a systematic review and meta-analysis.

OBJECTIVES: A substantial proportion of adults with locally advanced gastric cancer derive limited benefit from neoadjuvant chemotherapy (NAC), with a...

User evaluation of AI- and human-generated responses in digital health communication: a paired survey study.

BACKGROUND: Digital health communication is gaining importance as health care systems face increasing demand and structural constraints. Generative ar...

Factors Influencing Nursing Internship Students' Readiness to Use AI: Cross-Sectional Study Using Neural Network Analysis.

BACKGROUND: Enhancing nursing students' awareness, attitudes, beliefs, and preparedness toward AI may help improve their health care knowledge and pra...