Product Alert

Automated Post-Analytical Workflow for Newborn Screening Using a Hybrid Rule-Based and Retrieval-Augmented Large Language Model System.

Newborn screening using tandem mass spectrometry requires complex post-analytical workflows, including QC review, patient report generation, and cutoff reassessment, which are repetitive, time-consuming, and error-prone. We developed a Python-based clinical decision support system with a graphical user interface, integrating four functionalities: QC and patient result evaluation with deterministic...

A data-driven approach to define the stages and patterns of neurological recovery after traumatic spinal cord injury.

BACKGROUND: Recovery after spinal cord injury (SCI) follows a complex and variable trajectory, yet the field lacks clear, data-driven definitions of the temporal stages of recovery. This study aimed to model the trajectory of recovery after SCI and define distinct post-injury phases based on real-world clinical data. METHODS: We analyzed longitudinal data from 4407 individuals with traumatic SCI e...

Integrating Course-Based Competitions into Strategic Management Instruction: A Reproducible Course Improvement Protocol.

Strategic Management instruction requires students to apply analytical frameworks to uncertain, resource-constrained, and trade-off-based business sit...

Engineering innovations for precision medicine: sensors, AI biomarkers, and predictive interventions.

Precision medicine unifies the latest capabilities from engineering, biotechnology, and artificial intelligence (AI) to deliver data-driven personaliz...

ChatGPT-4o as a decision-support tool in a urological tumour board: a prospective evaluation.

PURPOSE: To evaluate ChatGPT-4o in a real-world urological multidisciplinary tumour board (MTB), with concordance for the final clinical recommendatio...

Cost-Effectiveness of an Artificial Intelligence as a Medical Device (AIaMD) for Triaging Patients Presenting to Primary Care with Concerns that They Have a Skin Cancer: A Modelling Study.

INTRODUCTION: Health services are struggling to cope with the growing numbers of people coming with skin lesions they are worried could be cancer. Usi...

Interpretable Machine Learning for 30-Day Mortality in PIVSR: A Cohort Study.

OBJECTIVE: Post-infarction ventricular septal rupture (PIVSR) is a fatal mechanical complication of acute myocardial infarction. We aimed to develop a...

Machine learning combined with fMRI identifies dynamic brain network alterations in post-stroke depression: A dual-center cross-sectional study.

OBJECTIVE: Post-stroke depression (PSD) is under-recognized and associated with poorer rehabilitation outcomes and quality of life. We characterized P...

Microfluidic Chip Platforms for Red Blood Cell Storage Lesion Quality Control and Precision Transfusion.

Red blood cell (RBC) transfusion is a core clinical intervention. However, hypothermic storage induces progressive biochemical, structural, and functi...

Deep-Learning Based Contrast Boosting: A Multi-Center Multi-Reader Study on Clinical Performance With Standard Contrast Enhanced Brain MRI.

BACKGROUND: Gadolinium-based contrast agents are used in brain MRI to improve the visualization of disorders and improve the delineation of lesions. H...

A Scoping Review of Interpretable AI Model Approaches in Echocardiography: Frameworks, Model Types, Explanation Strategies, and Evaluation Practices.

Echocardiography is a central modality for cardiac diagnosis; rising clinical demand and advances in machine learning have accelerated AI development ...

Large language models and prostate MRI reporting: a stringent testbed for safe deployment under evolving AI, health-data, and cybersecurity regulation.

Prostate magnetic resonance imaging (MRI) reporting is a high-impact communication task because small differences in lesion laterality, sector localiz...

An AI-Supported Virtual Patient Application Using a Structured Prompting Framework to Develop Mental Status Examination Skills in Psychiatric Nursing Internship Students: An Interventional Mixed-Methods Study.

The aim of this study is to evaluate the effect of an artificial intelligence (AI)-powered virtual patient application (ChatGPT) on the development of...

AI-generated patient instructions as safety-critical communication: a provisional evidence-informed framework for clinical deployment.

Generative artificial intelligence (AI) can convert clinical information into patient-facing instructions, including discharge summaries, medication e...

Federated learning for MRI-based BrainAGE: A multicenter study on post-stroke functional outcome prediction.

OBJECTIVE: Brain-predicted age difference (BrainAGE) is a neuroimaging biomarker reflecting brain health, with potential implications for post-stroke ...

When algorithms don't care: physiotherapy and the post-professional turn.

Physiotherapy has long resisted the forces that restructured manufacturing, journalism, and finance. This resistance is ending. Drawing on Gilles Dele...

Integrating Generative AI Into Clinical Reasoning Education for Medical Students: Mixed Methods Study.

BACKGROUND: Generative AI (GenAI) is increasingly integrated into clinical learning and practice. However, medical students often lack the competencie...

Prediction in routine care: a naturalistic comparison of clinicians and a machine learning model for patients receiving treatment for generalised anxiety disorder.

OBJECTIVE: Approximately half of patients with generalised anxiety disorder (GAD) do not recover following psychological treatment. Accurate prognosti...

Evaluation of an AI-powered tool in improving lesion visualization on standard-dose contrast-enhanced brain MRI: a retrospective, multicenter study.

BACKGROUND AND PURPOSE: Artificial intelligence (AI) algorithms have been used to synthesize standard-dose images from low-dose images in brain MRI, b...

Volumetric Assessment of Vestibular Schwannomas Exhibiting Internal Growth After Stereotactic Radiosurgery: Application of Artificial Intelligence.

PURPOSE: Vestibular schwannomas (VS) are monitored for growth after stereotactic radiosurgery (SRS) using serial MRI. Conventional measurements often ...