Risk Management

Legal implications of artificial intelligence in health care.

The last few years have seen a boom in the popularity of artificial intelligence (AI) around the world, and the health care sector has not been immune from what has been perceived by some as a revolutionary technology. Although AI has been around for many years, including in the field of health care, the recent introduction of consumer-facing generative AI tools has put a spotlight on the technolo...

Protocol for performing deep learning-based fundus fluorescein angiography image analysis with classification and segmentation tasks.

Fundus fluorescein angiography (FFA) examinations are widely used in the evaluation of fundus disease conditions to facilitate further treatment suggestions. Here, we present a protocol for performing deep learning-based FFA image analytics with classification and segmentation tasks. We describe steps for data preparation, model implementation, statistical analysis, and heatmap visualization. The ...

Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HEAT Center study protocol.

INTRODUCTION: African cities, particularly Abidjan and Johannesburg, face challenges of rapid urban growth, informality and strained health services, ...

Systematic review of machine learning models in predicting the risk of bleed/grade of esophageal varices in patients with liver cirrhosis: A comprehensive methodological analysis.

Esophageal varices (EV) in liver cirrhosis carry high mortality risks. Traditional endoscopy, which is costly and subjective, prompts a shift towards ...

An Experiment Using Functional Near-Infrared Spectroscopy and Robot-Assisted Multi-Joint Pointing Movements of the Lower Limb.

Stroke affects approximately 17 million individuals worldwide each year and is a leading cause of long-term disability. Robotic therapy has shown prom...

Does an App a Day Keep the Doctor Away? AI Symptom Checker Applications, Entrenched Bias, and Professional Responsibility.

The growing prominence of artificial intelligence (AI) in mobile health (mHealth) has given rise to a distinct subset of apps that provide users with ...

Role of Artificial Intelligence in Improving Syncope Management.

Syncope is common in the general population and a common presenting symptom in acute care settings. Substantial costs are attributed to the care of pa...

Feature group partitioning: an approach for depression severity prediction with class balancing using machine learning algorithms.

In contemporary society, depression has emerged as a prominent mental disorder that exhibits exponential growth and exerts a substantial influence on ...

Geometry Optimization Algorithms in Conjunction with the Machine Learning Potential ANI-2x Facilitate the Structure-Based Virtual Screening and Binding Mode Prediction.

Structure-based virtual screening utilizes molecular docking to explore and analyze ligand-macromolecule interactions, crucial for identifying and dev...

Can Artificial Intelligence Accurately Detect Urinary Stones? A Systematic Review.

To perform a systematic review on artificial intelligence (AI) performances to detect urinary stones. A PROSPERO-registered (CRD473152) systematic s...

Liability of Health Professionals Using Sensors, Telemedicine and Artificial Intelligence for Remote Healthcare.

In the last few decades, there has been an ongoing transformation of our healthcare system with larger use of sensors for remote care and artificial i...

A joint training of healthcare line managers and health and safety representatives in facilitating occupational health interventions: a feasibility study protocol for the Co-pilot project.

Healthcare employees are experiencing poor wellbeing at an increasing rate. The healthcare workforce is exposed to challenging tasks and a high work p...

Performance of an ultra-fast deep-learning accelerated MRI screening protocol for prostate cancer compared to a standard multiparametric protocol.

OBJECTIVES: To establish and evaluate an ultra-fast MRI screening protocol for prostate cancer (PCa) in comparison to the standard multiparametric (mp...

Assessment of image quality and impact of deep learning-based software in non-contrast head CT scans.

In this retrospective study, we aimed to assess the objective and subjective image quality of different reconstruction techniques and a deep learning-...

DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks-a prospective observational study using digital markers and artificial intelligence-study protocol.

INTRODUCTION: Asthma attacks are a leading cause of morbidity and mortality but are preventable in most if detected and treated promptly. However, the...

Effectiveness of artificial intelligence vs. human coaching in diabetes prevention: a study protocol for a randomized controlled trial.

BACKGROUND: Prediabetes is a highly prevalent condition that heralds an increased risk of progression to type 2 diabetes, along with associated microv...

Artificial intelligence and endo-histo-omics: new dimensions of precision endoscopy and histology in inflammatory bowel disease.

Integrating artificial intelligence into inflammatory bowel disease (IBD) has the potential to revolutionise clinical practice and research. Artificia...

Protocol to perform integrative analysis of high-dimensional single-cell multimodal data using an interpretable deep learning technique.

The advent of single-cell multi-omics sequencing technology makes it possible for researchers to leverage multiple modalities for individual cells. He...

Evaluation of image quality on low contrast media with deep learning image reconstruction algorithm in prospective ECG-triggering coronary CT angiography.

To assess the impact of low-dose contrast media (CM) injection protocol with deep learning image reconstruction (DLIR) algorithm on image quality in c...

Use of artificial intelligence in obstetric and gynaecological diagnostics: a protocol for a systematic review and meta-analysis.

INTRODUCTION: Emerging developments in applications of artificial intelligence (AI) in healthcare offer the opportunity to improve diagnostic capabili...