Risk Management

Applications of Large Language Models in Ovarian Cancer Management: Protocol for a Systematic Review and Meta-Analysis.

BACKGROUND: Ovarian cancer (OC) is a highly fatal gynecologic malignancy with complex management challenges and limited long-term survival for advanced stages. Large language models (LLMs)-including systems such as GPT-4, Claude, Google Gemini, and others-are emerging artificial intelligence (AI) tools capable of performing health care-related tasks such as diagnostic support, treatment planning, ...

Air pollution and autism-like traits: sensitive periods and joint effects of exposure to sources and constituents of fine particulate matter.

Growing evidence suggests that exposure to air pollution during early life is associated with autism spectrum disorder (ASD). However, results have been inconsistent for autism-like traits and in low exposure settings. Here, we assessed sensitive windows of exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) and joint effects of exposure to sources and constituents ...

Development of a machine learning-based model for predicting adverse pregnancy outcomes in women with polycystic ovary syndrome (PCOS): a retrospective observational study protocol.

INTRODUCTION: Polycystic ovary syndrome (PCOS) is a prevalent endocrine condition in reproductive-aged women, which is associated with adverse materna...

Registered AI Medical-Imaging Clinical Trials on ClinicalTrials.gov: Publication Yield, Predictors, and Portfolio Evolution.

RATIONALE AND OBJECTIVES: Although artificial intelligence (AI) clinical trials in medical imaging have grown rapidly, peer-reviewed publication outco...

Cross-scenario evaluation of explainable machine learning for non-invasive summer occupancy detection across five building scenarios.

Accurate identification of indoor occupant presence is crucial for intelligent building energy management. Traditional monitoring methods are often in...

Knee-specific bone quality assessment for cementless total knee arthroplasty candidate selection: a narrative review.

Cementless total knee arthroplasty (TKA) has regained attention in younger, active, and obese patients, supported by advances in implant design, porou...

Trustworthy AI for personalized glycemic control: a systematic review and critical appraisal of multimodal forecasting and safety-critical closed-loop control.

Tight glycemic control reduces acute complications (hypoglycemia, hyperglycemia) and long-term microvascular/macrovascular risks. The application of A...

Portraying Ethical Risks of Medical AI: Mixed Methods Study From Connotation Definition to a Survey on Physicians' Cognition.

BACKGROUND: Ethical risks of medical artificial intelligence (AI) are a global concern, but existing understanding remains fragmented without an integ...

Development and validation of a disease-syndrome integrated assessment model for AECOPD severity: protocol for a nationwide multicentre cross-sectional study.

INTRODUCTION: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) accelerate disease progression and increase mortality. Accurate se...

Machine Learning-Based Privacy Preserving via CT/MRI and Organ Metadata Prediction.

Medical imaging plays a significant role in diagnosis and treatment planning, with significant efforts focused on training machine learning (ML) algor...

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' rel...

Large Language Models in Preclinical Spine Research: A Scoping Review and Expert Perspective on Evidence-Aware Experimental Workflows.

BACKGROUND: Preclinical spine research is limited by heterogeneous experimental reporting, fragmented documentation, and barriers to reproducibility a...

Deep learning-assisted chrysotile asbestos screening in soil: A hierarchical statistical approach to error propagation.

Manual polarized light microscopy (PLM) is widely used for asbestos screening in soil, yet the technique remains labor-intensive and susceptible to in...

SERSome-based metabolic profiling of aqueous humor for cataract subtyping with molecule-level interpretability.

Cataract is among the leading cause of vision impairment worldwide and it is essential to uncover molecule-level characteristics of different cataract...

Conceptualization, Operationalization, and Measurement of Adherence to Patient-Facing Digital Health Applications: Protocol for a Scoping Review.

BACKGROUND: Medical adherence is traditionally defined as the extent to which a person's behavior corresponds with agreed-upon recommendations from a ...

Service Robots as Work Support for Health Personnel in Long-Term Care: Protocol for a Scoping Review.

BACKGROUND: Demographic shifts are increasing the global demand for long-term care services, coinciding with a worldwide shortage of health care perso...

MRI-Only Simulation for Prostate MRI-Guided SBRT.

PURPOSE: The SMART (Stereotactic MR-Guided Adaptive Radiation Therapy) protocol for prostate SBRT has demonstrated favorable clinical outcomes using a...

Leveraging a vendor-neutral deep learning reconstruction algorithm to reduce scan time and enhance image quality in T2-weighted liver MRI.

This study evaluated whether a vendor-neutral deep learning reconstruction (DLR) can improve image quality in accelerated T2-weighted imaging (T2WI) o...

Leveraging generative artificial intelligence for the development of non-interventional research study protocols: a proof-of-concept feasibility study.

BACKGROUND: The writing of study protocols is a labor and time-intensive process. We hypothesized that the writing of some methodological aspects of s...

Explainability in action: A metric-driven assessment of local explanations for healthcare tabular models.

Explainable AI (XAI) is increasingly used in clinical machine learning, yet quantitative evaluation of explanation quality is often reported inconsist...