Surveys

Towards grey-zone reliability in CA19-9 nanobiosensing: an AI-integrated molecular interface design-to-decision framework.

Mildly elevated CA19-9 levels (typically 37-300 U mL-1) define a diagnostic grey zone that fuels both patient anxiety and overdiagnosis, yet many nanobiosensing works continue to prioritise ever-lower detection limits over clinical reliability in this ambiguous interval. In this review, we argue for a use-case-specific shift from sensitivity-only reporting to reliability-centred translational nano...

Evaluating large language models in patient education: a comparative analysis addressing frequently asked questions in peri-acetabular osteotomy.

INTRODUCTION: Large language models (LLMs) are increasingly used as sources of information across many fields, including healthcare. As patients turn to these models for health-related queries, evaluating the accuracy and reliability of their responses is essential. Peri-acetabular osteotomy (PAO) is performed on younger patients - a group more likely to use digital tools like LLMs for health info...

SSS Framework: A Think-First, AI-Second Model for AI-Assisted Writing.

It is remarkable how quickly AI has become woven into the ways we think, write, and create, bringing renewed attention to intellectual autonomy and th...

Rehab or not rehab: artificial intelligence helps humans identify rehabilitation Cochrane systematic reviews.

BACKGROUND: Rehabilitation is a core component of health systems worldwide, yet its conceptual boundaries remain heterogeneous and difficult to operat...

Concerning uncertainty-a systematic survey of uncertainty-aware XAI.

This paper surveys uncertainty-aware explainable artificial intelligence (UAXAI), examining how uncertainty is incorporated into explanatory pipelines...

The interplay between Bayesian inference and conformal prediction.

Conformal prediction (CP) has emerged as a cutting-edge methodology in statistics and machine learning, providing prediction intervals with finite-sam...

Performance of Large Language Models in Oral Cancer Patient Education: An Evaluation of Reliability, Readability, and Patient Communication Quality.

BACKGROUND: As society is increasingly depending on large language models (LLMs) for health-related questions, it is essential to objectively evaluate...

Integrating Environmental Exposure Profiles with Temporal Transcriptomics: An Explainable Machine Learning Model for Cardiovascular Disease Risk Prediction and Biological Validation.

BACKGROUND: Cardiovascular disease (CVD) pathogenesis is strongly associated with environmental exposures and metabolic factors. This study aimed to i...

Artificial Intelligence in Pharmacovigilance: Guiding Principles from the CIOMS Working Group XIV.

Artificial intelligence (AI) is increasingly being explored to support pharmacovigilance activities including processes involving individual case safe...

Quality and reliability of YouTube videos on PET/CT radiation safety: a comparative analysis between human experts and large language models.

PURPOSE: To evaluate the quality and accuracy of YouTube videos regarding PET/CT radiation safety and to assess the feasibility of using a Large Langu...

Artificial intelligence responses to toilet training questions: A reliability and readability analysis of ChatGPT and gemini applications.

BackgroundToilet training is a critical developmental milestone that may have long-term implications for children's psychosocial development if improp...

CT scan range planning in clinical practice: An international survey of scan range extension, quality assurance, and AI integration.

INTRODUCTION: Computed tomography (CT) scan range planning is a modifiable determinant of radiation exposure but remains highly variable in clinical p...

Precision Education: How Ready Are Obstetrics and Gynecology Clerkships for the Future of Medical Education?

OBJECTIVES: Precision education has been heralded as the future of medical education, yet substantial barriers to realizing this future exist. We soug...

Reinventing the echocardiography workflow: from manual quantification to artificial intelligence-driven comprehensive interpretation.

Echocardiography remains the cornerstone of cardiovascular imaging. However, traditional workflows including manual acquisition, sequential measuremen...

Generative Artificial Intelligence Performance on University-Level Human Anatomy Examinations: A Structured Narrative Review and Proposed MATRIX-Anatomy Framework.

Generative artificial intelligence (GenAI) can perform strongly on written anatomy examinations, but whether such scores represent anatomical competen...

A clinician-centered evaluation framework for large language models in patient education: Integrating the Technology Acceptance Model and Medical Condition Regard Scale.

Inadequate post-care patient education contributes to preventable readmissions and adverse outcomes that disproportionately affect medically complex, ...

Understanding the Functional Needs of Patients With Cardiovascular Disease Regarding Nursing Robots Using a Kano Survey Scale: Cross-Sectional Study.

BACKGROUND: With population aging and the growing burden of chronic diseases, the number of patients with cardiovascular disease (CVD) in China contin...

Patients' Perspectives on Applications of AI and Personalized Medicine in Life-Threatening Heart Disease: European Cross-Sectional Patient Questionnaire Study.

BACKGROUND: The growing integration of personalized risk prediction (PRP) and AI substantially reshapes diagnostic and therapeutic decision-making in ...

Attitudes, perceptions, and UTAUT-based factors influencing the acceptance of medical artificial intelligence among Chinese oncology healthcare professionals: a national cross-sectional survey.

OBJECTIVES: To conduct a nationwide survey among professionals working in oncology departments in China to investigate their attitudes, perceptions, a...

An Umbrella Review of Artificial Intelligence Applications in Mental Health Care.

BACKGROUND: Artificial intelligence (AI) is increasingly used in mental health care to address rising demand, workforce shortages and access barriers;...