Surveys

Usability and Usefulness of Machine Learning-Based Clinical Decision Support Software in Primary Care: Survey of Users in a Prospective Observational Study.

BACKGROUND: The successful implementation of decision support systems promises to enhance high-quality care. However, the successful implementation of a clinical decision support system (CDSS) depends on user acceptance and adoption. A machine learning (ML)-based CDSS to assist primary care professionals treating urinary tract infections (UTIs) was implemented, and usability and usefulness were as...

Artificial intelligence for reducing metal artifacts in dental CBCT images: a systematic review.

OBJECTIVES: The presence of metallic restorations introduces severe artifacts that compromise diagnostic accuracy of cone beam computed tomography (CBCT) images. This systematic review aims to evaluate the effectiveness of artificial intelligence (AI) techniques in reducing metal artifacts in dental CBCT images. METHODS: A comprehensive literature search was conducted across six databases up until...

Evaluation of ChatGPT-5-generated surgical literature: the accuracy of a review on penile prosthesis implantation.

The integration of artificial intelligence language models into medical literature requires rigorous evaluation of accuracy and reliability, especiall...

Reliability and readability of AI platforms for pediatric health advice: a comparative analysis.

Large language models (LLMs) are increasingly used as a first-line source of information for everyday questions, including pediatric health guidance, ...

Missing data imputation in hourly CO measurements for air quality monitoring: a case study in the city of Salvador, Brazil.

Continuous and uninterrupted air quality monitoring is essential for environmental management and public policy formulation, which requires the absenc...

Transformation of artistic style and innovative design of oriental folk patterns based on AIGC Technology-A case study of Zhuxian town new year paintings from China.

In response to the limited cross-domain innovation in the digitalization of traditional oriental folk art, this study takes the New Year pictures of C...

Artificial intelligence in population-based cancer screening: evidence from a national survey of Italian professionals.

BACKGROUND: Artificial Intelligence (AI) is increasingly proposed to enhance population-based cancer screening. While several applications are under e...

Assessing the trustworthiness of health guidelines recommendations: the Transparent, Rigorous, Usable, Standardised and Trustworthy Guide (TRUSTGUIDES) tools development.

BACKGROUND: Health guidelines play a central role in informing clinical practice, public health measures and health policy. But their trustworthiness ...

Predicting immune checkpoint inhibitor cardiotoxicity using machine learning: a systematic review of model performance and methodological quality.

BACKGROUND: Immune checkpoint inhibitors (ICIs) significantly improve cancer outcomes but can cause rare, potentially fatal cardiotoxicity, including ...

Cultural bias in large language models' ability to follow neuroradiology guidelines.

OBJECTIVES: Large language models (LLMs) are increasingly explored as decision-support tools in medical imaging. However, their ability to align with ...

'Man vs. Machine: can ML algorithms diagnose headaches as accurately as clinicians? A systematic review.'.

BACKGROUND: Headache disorders are frequently misdiagnosed. We aimed to systematically evaluate the diagnostic accuracy, methodological quality, and c...

When AI Colludes: Clinical Reliability of Training and Preference Data as a Trustworthy-AI Criterion.

Research on artificial intelligence (AI) and mental health has focused largely on harms at deployment, including chatbot safety, sycophancy, and AI-as...

Addendum to "Predicting treatment pathways in Class II malocclusion patients using machine learning: A comparative study of four algorithms for classifying camouflage, growth modulation, and surgical decisions" [Int Orthod. 24 (2026) 101070].

OBJECTIVES: The aim of this study was to develop a machine learning model to assist in treatment decision-making for surgery, camouflage, and growth m...

Explainability in context: calibrating appropriate trust and reliance in artificial intelligence.

BACKGROUND AND SIGNIFICANCE: Predictive artificial intelligence (AI) promises to transform care delivery, enhance patient safety, and improve health o...

A translational IoT healthcare framework integrating secure sensing, energy-aware intelligence, and adaptive emergency response.

The Internet of Things (IoT) is transforming the healthcare industry by enabling real-time patient monitoring, predictive analytics and smart decision...

Automated assessment of coronal lower extremity alignment on long-leg radiographs using a deep-learning model: validation, efficiency gains, and superiority of an edge-based tibial joint-line definition.

PURPOSE: To develop, validate, and benchmark a fully automated deep learning (DL) system that simultaneously measures 15 coronal lower-limb alignment ...

A pragmatic measure of student-reported school climate: How low can you go?

There continues to be great interest in efficient and valid methods for assessing school climate for both research and practice purposes. Consistent w...

Evaluating Injection Laryngoplasty Skills Using a Foundation Model: A Feasibility Study.

OBJECTIVES: To evaluate the construct validity of a commercially available multimodal foundation model (Google Gemini 2.5 Pro) in assessing simulated ...

Learning From Crowds With Multiple Feature Dynamic Fusion-Based Annotation Generation.

As the scale of data grows for machine learning, annotating data accurately is extremely time-consuming and with high economic costs. To alleviate thi...

BiasField: Interactive Bias Probing of Machine Learning Datasets.

Bias in machine learning datasets occurs when certain attributes are unfairly associated, e.g., serious males being mostly linked with law enforcement...