Risk Management

Application value of gastric contrast ultrasonography in gastric tumors.

In recent years, gastric oral contrast ultrasonography (OCUS) and double contrast-enhanced ultrasonography (DCEUS) have emerged as promising imaging techniques for evaluating gastric tumors, particularly gastric cancer (GC), by providing beneficial insights into tumor morphology, vascular characteristics and response to therapy. OCUS is capable of identifying the thickened gastric wall and lesions...

Molecular and Pharmacogenetic Marker Evaluation in Relation to the Toxicity and Clinical Response of Acute Lymphoblastic Leukemia Treatment in Indian Children (MPGx-INDALL): Protocol for a Prospective Observational Cohort Study.

BACKGROUND: Understanding interindividual variability in treatment response and toxicity is essential for optimizing outcomes in pediatric acute lymphoblastic leukemia (ALL). Molecular and pharmacogenetic markers hold promise in predicting treatment efficacy and adverse effects, particularly in genetically diverse populations. This protocol outlines the methodology for a prospective, nonrandomized...

Accuracy of Diagnosis and Anticipation of Future Treatment in Pediatric Peripelvic Infections: The Role of Multisurgeon Review and Implications for Future Machine Learning Algorithms.

INTRODUCTION: MRI is commonly used to evaluate pelvic musculoskeletal infections. Limited "quick" MRI protocols enable timely imaging without intraven...

Automated Prediction of Radiological Protocols Using Retrieval Augmented Generation.

Radiological protocol selection is a critical but time-consuming step in clinical workflow, requiring radiologists to match patient indications with a...

Establishing the laboratory error database: rationale, methodology, and a practical example.

Laboratory errors represent a critical yet underestimated threat to patient safety, with 26-30 % of reported errors adversely affecting patient care. ...

CT acquisition protocols in lung cancer screening: implications for guideline development from a worldwide survey.

OBJECTIVES: To assess the currently applied CT image acquisition protocols in lung cancer screening (LCS) and thereby fill a knowledge gap to support ...

The economic imperative of artificial intelligence in maternal and neonatal health: a review of evaluation benefits, frameworks, challenges, future perspectives, and limitations.

Integrating artificial intelligence (AI) into maternal and neonatal health (MNH) offers significant opportunities for enhancing patient care through a...

Assessing the influence of kernel selection on chest computed tomography image quality across varying dose levels using TrueFidelity reconstruction.

Deep learning image reconstruction (DLIR) utilizes neural networks to generate high-quality computed tomography (CT) images. One commercially availabl...

Biosignatures of cognitive basic symptoms mark a distinct neurodevelopmental pathway to schizophrenia.

Efforts to predict schizophrenia risk using biological data have been hampered by the heterogeneity of current "clinical-high-risk" (CHR-P) criteria, ...

Initial experience of deep learning reconstruction algorithm in lung kernel: clinical usefulness for lung nodules at ultra-low-dose protocol.

OBJECTIVES: TrueFidelity (TF), a deep learning image reconstruction algorithm that was originally available only in standard kernel, has recently beco...

NeuroMix-DL: Improving imaging quality of a fast multiparametric MRI protocol using deep learning.

PURPOSE: To improve the quality of a fast multi-contrast MR protocol acquisition using deep learning. MATERIALS AND METHODS: 350 patients (age: 64 ± 1...

Definitions of early COPD and predictors for disease progression: a systematic review.

INTRODUCTION: Early chronic obstructive pulmonary disease (COPD) is considered to represent the initial phase of the disease. However, inconsistent te...

Robust prediction of parameterized cardiovascular hemodynamics using deep operator networks with time normalization.

BACKGROUND AND OBJECTIVES: Computational modeling of cardiovascular hemodynamics is essential for understanding disease mechanisms. While one-dimensio...

Artificial intelligence-powered models in predicting mortality in maternal, newborn, and children under five: a systematic review protocol.

BACKGROUND: Maternal, newborn, and under-five mortality remain significant global health challenges, with 287,000 maternal deaths reported in 2020 and...

VISTA-3D : Training-free unfolding for vision-based 3D object detection.

3D object detection from vision inputs powers autonomous driving and embodied AI but remains compute- and energy-intensive at inference. While neuromo...

Improved image quality and reduced acquisition time in brain MRI using deep learning-based reconstruction: A quantitative and subjective assessment compared to standard MPRAGE in 0.55 T MRI.

PURPOSE: To assess the impact of deep learning (DL)-based image reconstruction on quantitative and subjective image quality in brain MRI at 0.55 T by ...

An AI-assisted framework for the ethical use of machine learning in healthcare.

This study develops and evaluates ETHICS, a concise, clinician-facing ethical protocol for the routine use of machine learning (ML) in healthcare. Usi...

Common factors and unique pathways for linkages between HIV/STI prevention and syndemic behaviours in high-risk youth: protocol for a secondary analysis of harmonised data from six clinical trials.

INTRODUCTION: HIV/sexually transmitted infection (STI) prevention interventions are only modestly successful among youth, particularly for young peopl...

Speech-to-Speech Voice-Cloning Care (SVCC) for improving ICU-acquired anxiety for critically ill patients in a tertiary hospital in Beijing, China: protocol of a randomised, controlled trial.

INTRODUCTION: Intensive care unit (ICU) visiting restrictions in hospitals, implemented due to infection control and other factors, limited contact be...

Evaluation of the level of responsibility in pedestrian crashes using machine learning algorithms.

Traffic crashes involving pedestrians tend to result in the most casualties (minor, serious, or fatal). Therefore, accurately determining the level of...