Risk Management

Video-Based Gait Assessment Using Machine Learning to Classify Age and Sex in Low-Resource Settings: Cross-Sectional Study.

BACKGROUND: Gait assessment is an important tool for evaluating health risks in older adults but remains underused in low-resource settings. We explored the feasibility of using a low-cost, simple walking protocol with smartphone video capture to extract health-related gait signals by classifying sex and age. Sex and age are fundamental biological factors linked to most health- and aging-related o...

ECG-Gated Retrospective Coronary CT Angiography With Deep Learning Reconstruction on 8-cm Detector CT Scanners: Pushing Radiation Dose Towards Prospective Acquisition on 16-cm Wide-Detector Scanners.

PURPOSE: Although 16-cm wide-detector CT scanners with prospective ECG-gating enable coronary artery imaging within a single cardiac cycle at a low radiation dose, many institutions still rely on scanners with detector widths <16 cm. These scanners typically use retrospective scanning, resulting in higher radiation exposure. This study tests the feasibility of lowering the radiation dose of ECG-ga...

Artificial intelligence and radiomics for pediatric brain tumor classification and molecular characterization: a systematic review.

BACKGROUND: Artificial intelligence (AI) and radiomics are increasingly applied in pediatric neuroradiology to enhance diagnostic precision. However, ...

Measuring Accuracy (Classification Probabilities, Positive, and Negative Predictive Values) of Executive Function Electroencephalogram Metrics in Attention-Deficit/Hyperactivity Disorder Diagnosis: Protocol for and Perspectives From the SINCRONIA Study.

BACKGROUND: Attention deficit/hyperactivity disorder (ADHD) is the most prevalent neurodevelopmental disorder worldwide, affecting approximately 5%-7%...

Kenyan Neonatal Mortality Risk Predictor: Protocol for a User-Centered Design Evaluation.

BACKGROUND: Neonatal mortality remains a major public health challenge in low- and middle-income countries (LMICs), particularly in sub-Saharan Africa...

Beyond the Hype: Understanding the Limits, Errors and Risk Areas of Artificial Intelligence in Gastroenterology.

Artificial intelligence (AI) has rapidly expanded across gastroenterology, enabling advances in real-time endoscopic detection, radiologic interpretat...

Baseline symptom severity and response to multisession cathodal transcranial direct current stimulation in adolescents and young adults with autism: an exploratory analysis.

BACKGROUND: Identifying baseline clinical characteristics associated with treatment response is crucial for optimising intervention strategies in peop...

A comprehensive analysis of brain network complexity in task-based fMRI using entropy: systematic review.

Entropy-based analysis is increasingly used in task-based functional magnetic resonance imaging (fMRI) to quantify neural signal complexity and inform...

Could ChatGPT and co. replace forensic experts? A comparative study on medical liability expertise.

Artificial intelligence is expected to play an increasingly significant role in both medicine and law. The performance of generative artificial intell...

How does the implementation of AI-based automation of administrative tasks affect healthcare professionals' work? Study protocol for a longitudinal embedded case study in Swedish primary and specialist care.

INTRODUCTION: Artificial intelligence (AI) is transforming healthcare through enhanced computational capabilities that process vast amounts of data wi...

Capacity building for ethical use of artificial intelligence in health: protocol for a scoping review of training initiatives and gaps in Africa.

INTRODUCTION: Artificial intelligence (AI) is increasingly embedded in health systems, with applications spanning diagnostic imaging, clinical decisio...

Machine Learning Models Used to Predict Abdominal Aortic Aneurysm Growth and Rupture: A Systematic Review and Critical Appraisal.

BACKGROUND: Abdominal aortic aneurysm (AAA) rupture remains a major cause of mortality, and diameter-based surveillance is an imperfect predictor of r...

Deep convolutional neural networks for age and gender estimation using orthopantomogram images: a systematic review.

OBJECTIVE: The primary goal of this systematic review is to critically analyze and evaluate how effectively deep convolutional neural networks (CNNs) ...

Fuzzy Logic Approaches for Causal Inference in Health Care: Systematic Review.

BACKGROUND: Fuzzy logic has been progressively investigated as a viable alternative to traditional statistical and machine learning methods in health ...

Long-term outcomes of lateral sinus floor elevation: A machine-learning analysis, systematic review, and meta-analysis of predictive factors.

OBJECTIVES: To quantify long-term (≥ 5 years) implant survival after lateral sinus floor elevation (LSFE) and to identify clinical predictors of long-...

Overall risk of cancer incidence attributable to adult body CT examinations: impact of a seven-year continuous quality improvement program.

OBJECTIVES: To estimate the impact of a continuous dose reduction and quality improvement program on radiation-induced cancer risk in adult computed t...

Longitudinal and Multimodal Recording System to Capture Real-World Patient-Clinician Conversations for AI and Encounter Research: Protocol for an Observational Study.

BACKGROUND: The promise of artificial intelligence (AI) in medicine depends on its ability to learn from data that reflect what matters to patients an...

Differential Factors Associated With the Presence of Persistent Symptoms in Individuals Diagnosed With Long COVID: Protocol for a Longitudinal Matched Case-Control Study.

BACKGROUND: Long COVID (postacute sequelae of SARS-CoV-2 infection) is a heterogeneous condition with persistent multisystem symptoms and substantial ...

Postgraduate students' perceptions of artificial intelligence integration in research: A cross-sectional study.

BACKGROUND: Generative artificial intelligence (AI) tools such as ChatGPT are increasingly used in academic research, yet evidence on postgraduate stu...

Softwar-defined vehicle network security using blockchain approach.

Software-Defined Vehicular Networks (SDVNs) are important in facilitating intelligent transport systems since vehicles communicate with infrastructure...