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Generalizing Drug-Drug Interaction Risk Prediction to Chemically Novel Compounds with Bilinear Interaction Learning and Calibrated Hybrid Inference.

Reliable drug-drug interaction (DDI) prediction is essential for polypharmacy safety and for prioritizing risky combinations during early-stage drug discovery. A persistent obstacle is inductive generalization: models that perform well under convenient i.i.d. splits often degrade when evaluated on chemically novel compounds. In addition, some feature sets used in prior work can inadvertently encod...

Preliminary evaluation of an AI-enhanced simulated interprofessional learning intervention for pharmacy students: a mixed-methods pilot study.

BACKGROUND: Interprofessional education (IPE) is vital for preparing pharmacy students for collaborative practice but is often constrained by logistical challenges. This study examined the preliminary impact of an AI-enhanced simulated interprofessional learning intervention on pharmacy students' self-reported interprofessional competencies and perceived readiness for AI use in healthcare, using a...

Impact of middle meningeal artery embolization on neurological complications and discharge outcomes in chronic subdural hematoma: A machine learning-based comparative study.

INTRODUCTION: Chronic subdural hematoma (cSDH) predominantly affects older adults, often those with prior head trauma, anticoagulation therapy, or chr...

AI-Based Post-processing for Artefact Mitigation in Radiography: A Systematic Review.

Projectional radiography is vulnerable to artefacts that can impair image quality and obscure or mimic pathology, confounding image interpretation. Th...

AI-based virtual patient training for clinical communication skills in dental undergraduates: A randomized controlled mixed methods study.

INTRODUCTION: Effective clinical communication is a core competency in dental education, yet traditional teaching methods often fail to provide authen...

Exploring the gut-lung axis in post-liver transplant acute lung injury: A multi-omics approach.

Acute lung injury (ALI) is a significant post-operative complication of liver transplant (LT), with mounting evidence suggesting a role for the gut-lu...

Integrating generative AI in EFL classrooms: A mixed-methods study on argumentative writing performance, writing enjoyment and motivation.

Writing in English as a Foreign Language (EFL) is widely recognized as one of the most challenging skills for language learners, and recent advances i...

Auricular Point Acupressure Self-Management (APA-SM) program for chronic musculoskeletal pain among rural populations: a protocol for a pragmatic, randomized controlled trial.

INTRODUCTION: Chronic musculoskeletal pain (CMP) is a leading cause of incurred personal healthcare costs and disability in the USA. It disproportiona...

Utilization of Heritage Manifestations in a Reminiscence Programme (App) Directed at Older Adults with and Without Neurocognitive Disorder, Employing AI: A Pilot Study in Portugal and Spain.

Cultural and intangible heritage has been part of human daily life since time immemorial, fulfils a function within the community and acts as an eleme...

Responsible AI Off-Boarding in Radiology: Staff Perspectives on Decommissioning and a Proposed Withdrawal Framework.

PURPOSE: AI governance commonly emphasises procurement, validation, deployment and performance monitoring but lack guidance on how embedded AI tools s...

History repeats in sweet solutions: toxicological concerns and targeted recommendations following the cough syrup-linked paediatric mortalities in India.

The latest episode of cough syrup-associated pediatric deaths in India linked to the reported diethylene glycol (DEG) contamination reverberates a lon...

A Coarse-to-Fine DoubleUNet Framework with Synergistic Loss for Accurate Fetal Head Circumference Measurement.

OBJECTIVE: Fetal head circumference (HC) measurement is a routine and indispensable examination during pregnancy, closely associated with fetal health...

An interpretable machine-learning model for post-admission reassessment of bloodstream infection risk in ICU patients with pneumonia.

The aim of this study is to develop and validate a machine learning-based predictive model to assess the risk of acquired bloodstream infection (BSI) ...

Cardiac magnetic resonance in patients with acute myocardial infarction: The added clinical value.

Cardiovascular magnetic resonance (CMR) has emerged as the reference noninvasive modality for a comprehensive assessment of myocardial injury followin...

Impact of Availability of Computer-Aided Detection Devices on Adenoma Detection During Colonoscopy: A Cluster Randomized Study.

BACKGROUND AND AIMS: Endoscopists' colonoscopy adenoma detection rates (ADR) are inversely associated with their patients' risk of post-colonoscopy co...

Performance Evaluation of GPT-5, Grok 4, and DeepSeek R1 in Interpreting Complete Blood Count Reports for Hematologic Diseases: Retrospective Comparative Study.

BACKGROUND: Large language models (LLMs) demonstrate potential in the laboratory, yet rigorous clinical evaluation remains limited. The opacity of LLM...

Developing and Testing a Brief Mindfulness Just-in-Time Adaptive Intervention to Reduce Stress Among Caregivers of People With Dementia: Quasi-Experimental Study.

BACKGROUND: Dementia caregiving entails chronic, fluctuating stress with downstream risks to caregivers' mental health and quality of care. Mindfulnes...

TASC: a time-aware sequence clustering framework with uncertainty quantification for electronic health record trajectories.

Longitudinal electronic health record (EHR) trajectories are highly heterogeneous, sparse, and irregular, making unsupervised temporal pattern discove...

Computational exploration of quercetin derivatives from Azadirachta indica leaf as threonine tyrosine kinase inhibitors for potential lung and pancreatic cancer treatment.

Lung and pancreatic adenocarcinomas account for substantial cancer-related mortality worldwide, with current therapeutic efficacy severely limited by ...

Early Immunological Biomarkers for Personalized Treatment Selection in Severe COVID-19: Post Hoc Machine Learning Analysis of a Randomized Clinical Trial.

BACKGROUND: Severe COVID-19 is a global health concern despite continuous vaccination campaigns because current therapies, such as dexamethasone and r...