Risk Management

Assessing Clinical Decision-Making Aided by a RAG-Based Dialog in Pre-Examination on Non-Odontogenic Tooth Pain.

Differentiating Non-Odontogenic Tooth Pain, a potential symptom of life-threatening conditions like Ischemic Heart Disease, is a critical challenge for dentists, as existing AI tools fail to support their decision-making. To address this, we developed a chatbot using a Retrieval-Augmented Generation (RAG) enhanced Large Language Model (LLM). This study protocol outlines a trial to evaluate the imp...

TrainTracks - federated learning for reproducible research on sensitive medical data.

BACKGROUND: Reproducibility of computational algorithms is a challenging but crucial requirement for medical research and an important component of trustworthy training and application of AI algorithms. Federated Learning (FL) is commonly used to enable privacy-preserving AI in medical research. One prerequisite of reproducibility is traceability. A majority of publications on traceable FL platfor...

Hyperbaric oxygen in the artificial intelligence era: integration and innovation.

Hyperbaric oxygen therapy is established for decompression illness, carbon monoxide poisoning, radiation-induced tissue injury, and diabetic foot ulce...

Acquisition time/dose reduction in pediatric PET imaging using patch-based deep learning.

BACKGROUND: Deep learning (DL)-based denoising methods have shown promise for reducing radiation dose and/or acquisition time in pediatric PET imaging...

Integrative Intelligence as an Operative Mode: Cognitive Integration through Self-Ethnographic Dialogue with AI.

This paper proposes Integrative Intelligence as an operative mode of human judgment in which temporal integration (past-present-future), contextual in...

[Artificial intelligence in urological surgery].

BACKGROUND: The integration of artificial intelligence (AI) into urological robotic surgery is currently in a dynamic phase of development and validat...

Mixed Reality and Desktop Hand Hygiene Training with Deep Learning-Based Step Recognition and Real-Time Decision Support.

Hand hygiene (HH) is essential for preventing healthcare-associated infections, yet conventional monitoring approaches primarily capture event occurre...

AJNR Study-Specific Guidelines for AI in Medical Imaging: Bridging Gaps in Reference Standard and Clinical Evaluation.

The rapid proliferation of artificial intelligence (AI) applications in neuroradiology can lead to heterogeneous study design and reporting that imped...

Evaluating the feasibility of a scalable, digitally supported model for global collaborative surgical research: protocol for a prospective, international, multicentre observational study in cryptoglandular anal fistula treatment (CRAFT).

INTRODUCTION: Management of cryptoglandular anal fistula is characterised by wide variation in diagnostic strategies, surgical techniques and outcome ...

A collaborative approach to applying Natural Language Processing (NLP) to Domestic Homicide Reviews (DHRs): A study protocol.

Since 2011, there has been a statutory requirement in England and Wales to conduct a Domestic Homicide Review (DHR) into any domestic abuse-related de...

Half-dose contrast media protocol using 70 kVp abdominal dynamic CT with super-resolution deep learning reconstruction: Evaluation of image quality and contrast performance.

OBJECTIVE: To evaluate contrast enhancement and image quality in 70 kVp abdominal dynamic CT using super-resolution deep learning reconstruction (SR-D...

The impact of generative artificial intelligence on clinical skills and knowledge acquisition in medical undergraduates: a systematic review and meta-analysis.

BACKGROUND: Currently, there is a growing body of research examining the role of generative Artificial Intelligence (GenAI) in medical undergraduate e...

An evidence-based nursing management app prototype for adult urology day surgery: an AI-driven development pathway.

OBJECTIVES: The nursing management of adult urology patients in day surgical settings has undergone rapid development. This study aimed to (1) retriev...

Development and Validation of a Deep Learning-enabled Single Breath-hold Abbreviated MRI Protocol for Hepatocellular Carcinoma Diagnosis.

Purpose To develop a deep learning-enabled single breath-hold abbreviated MRI (DL-SBH-aMRI) protocol for hepatocellular carcinoma (HCC) diagnosis. Mat...

Validity of AI-generated multiple-choice questions in medical education: a systematic review.

Large language models (LLMs) are increasingly used to generate multiple-choice questions (MCQs) in medical education. We conducted a systematic review...

HD-MUNet: integrating artificial intelligence and high-density electromyography for motor unit number estimation.

OBJECTIVE: In this study we developed and evaluated the performance of HD-MUNet: a novel method for motor unit number estimation (MUNE), integrating h...

Reliability-Aware Deep Learning Framework for Chemical Genotoxicity Prediction with Uncertainty Quantification.

Genotoxicity assessment is crucial for drug development and chemical safety evaluation. However, traditional experimental approaches are time-consumin...

Systematic review and meta-analysis of machine learning models predicting massive hemorrhage protocol in trauma.

Timely activation of massive hemorrhage protocols (MHP) is critical to prevent exsanguination and improve survival in trauma patients. Current clinica...

A clinically interpretable deep learning pipeline for diabetic retinopathy classification using EfficientNet, advanced data augmentation and GradCAM.

BACKGROUND: Early and reliable grading of diabetic retinopathy is important for preventing avoidable vision loss. Although deep learning methods have ...

Co-Lifecycle Governance for Learning Medical AI: A Hybrid Convergence Framework for Adaptive Regulatory Oversight.

Artificial intelligence (AI) in health care is increasingly defined not by static algorithms but by adaptive intelligence-systems that evolve over tim...