Risk Management

Hypoglycaemia Risk Prediction Models for Type 2 Diabetes: A Systematic Review and Meta-Analysis.

BACKGROUND: The growing number of hypoglycaemia risk prediction models for Type 2 diabetes mellitus (T2DM) underscores the need for systematic evaluation of their risk of bias and applicability. This study summarises and critically assesses their characteristics and predictive performance using established guidelines for prediction model development. METHODS: The review protocol was registered on ...

Deep Learning-Based Augmented Contrast-Enhancement and Denoising for Reduced-Iodine and Low-Radiation 70-kVp Cerebral CT Angiography: A Prospective Study.

OBJECTIVE: To evaluate the feasibility of cerebral computed tomography angiography (CTA) obtained with reduced iodine and low radiation at 70 kVp and the effect of deep learning-based augmented contrast enhancement (DL-ACE) and denoising (DL-DN) algorithms on the CTA quality. MATERIALS AND METHODS: In this prospective study, 47 healthy volunteers (male:female, 31:16; mean age ± standard deviation,...

Perceptions of clinicians and patients toward artificial intelligence applications in surgery: A scoping review.

BACKGROUND: Widespread adoption of artificial intelligence into surgical care heavily depends on clinician and patient attitudes, which remain poorly ...

Bridging the Gap Between Artificial Intelligence and Clinical Readiness in Endometriosis Diagnosis: A Systematic Review.

OBJECTIVE: To systematically evaluate the methodological quality and diagnostic performance of artificial intelligence (AI) applications, specifically...

Who's really in the loop? Rethinking oversight in AI-assisted health care.

Human-in-the-loop oversight is widely invoked as a safeguard against potential harm from artificial intelligence (AI) used in health care, yet it func...

Co-research in the development of AI and digital health tools for cancer management and care: a systematic review.

BACKGROUND: Participatory approaches (including co-research, co-design, Patient and Public Involvement [PPI], and Participatory Action Research [PAR])...

The challenge of bringing advances in sacroiliac joint imaging to the clinic.

PURPOSE OF REVIEW: Recently reported criteria are more stringent for classification of axial spondyloarthritis (axSpA) in the absence of positive imag...

Predicting early response to ablative radiotherapy in oligometastatic disease: a scoping review of radiomics-based machine learning and deep learning models.

OBJECTIVES: Oligometastatic disease represents an intermediate stage of cancer, often treated with surgery or ablative radiotherapy (ART). This scopin...

A multimodal EMG and IMU dataset for assessing the quality of exercises designed for spatially constrained environments.

Regular physical training is essential for maintaining physical fitness in environments where exercise must be performed in limited space and without ...

The evolving role of artificial intelligence in optimizing treatment and patient selection in diabetic macular edema.

Anti-vascular endothelial growth factor (anti-VEGF) therapy is the mainstay of management for diabetic macular edema (DME), but marked variability in ...

[Medicine and artificial intelligence. An ethical and legal perspective].

The development and use of artificial intelligence (AI)-supported medicine does not take place in a legal vacuum but within a traditional and well-est...

Legal liability of physicians and new governance in the AI era.

Veteran Monitoring Initiative for Noninvasive Physiology and Depression (V-MIND) Exploring Physical Activity and Mental Health in UK Veterans: Protocol for an Observational Digital Phenotyping Study.

BACKGROUND: Veterans face an increased risk of common mental disorders when compared to civilian groups. However, veteran disengagement from treatment...

Molecular characterisation of progressive pulmonary sarcoidosis: protocol for a longitudinal multi-centre study to develop peripheral blood circulating biomarkers for predicting pulmonary sarcoidosis progression.

INTRODUCTION: Sarcoidosis is a heterogeneous granulomatous disease with highly variable clinical trajectories, yet no validated biomarkers exist to di...

AgroDualNet: a dual deep learning-based crop disease forecasting and fruit ripening detection.

Proper diagnosis of crop diseases and accurate measurement of fruit ripeness is essential in enhancing agricultural productivity, but conventional met...

A pilot study on the impact of large language model assistance on the evaluation of complex medical living kidney donor candidates.

BACKGROUND: Large language models (LLMs) are undergoing exploration as clinical decision support tools. However, their role in complex, high-stakes tr...

A cross-sectional protocol for experimental tongue high-density surface electromyography to detect and classify radiation-associated hypoglossal neuropathy.

BACKGROUND: Hypoglossal neuropathy is the most common lower cranial neuropathy detected as a delayed sequelae of Human Papillomavirus (HPV) -driven or...

Patient Concerns Regarding Artificial Intelligence Applications in Health Care: Systematic Review and Meta-Synthesis Based on Social Ecological Theory.

BACKGROUND: The use of artificial intelligence (AI) in health care is growing quickly, but there is not enough research that looks at patient concerns...

Cost-effectiveness of infection prevention and control measures for carbapenem-resistant Gram-negative bacilli: A systematic review protocol.

INTRODUCTION: Multidrug-resistant organisms, including carbapenem-resistant Gram-negative bacilli (CRGNB), have a heavy health and economic burden in ...

Harnessing Artificial Intelligence for the Management of Patients With GI Cancers.

Artificial intelligence (AI) has the potential of reshaping GI oncology by enabling more nuanced interpretation of complex clinical, imaging, and mole...