Surveys

Using the Novel Translation Validity Index to Evaluate GenAI Translations of the Patient Health Questionnaire-9 Into Nine Languages.

Background and Purpose: Depressive symptoms affect 280 million people worldwide. Although generative artificial intelligence (GenAI) tools are increasingly used in health care translation, their translation performance across languages remains unclear. To our knowledge, no structured tool exists for evaluating the quality of language translation. This study aimed to create a translation validity i...

Multidimensional balance assessment and machine learning gait stability prediction in elderly women.

To develop and validate a comprehensive balance assessment scale specifically designed for elderly women and construct predictive models for gait stability outcomes using machine learning approaches. A total of 276 community-dwelling elderly women aged 60-80 years participated in this study. A multidimensional balance assessment scale was developed through expert consultation and psychometric eval...

Transforming hypoglycemia prediction in adult type 1 diabetes: a systematic review and meta-analysis for precision care.

Type 1 diabetes mellitus (T1DM) patients require lifelong insulin therapy; however, iatrogenic hypoglycemia remains a major clinical challenge, with h...

A remote monitoring system based on deep learning for real-time assessment of free flaps.

PURPOSE: Venous congestion is a major cause of postoperative free flap compromise, and early detection is crucial for improving flap salvage rates and...

Interpretable machine learning with SHAP analysis identifies redox-modulating dietary antioxidants for predicting accelerated biological aging.

BACKGROUND: Aging is a complex biological process characterized by progressive functional decline across multiple physiological systems, and biologica...

AI In the Chair: ChatGPT In Dental Education-A Cross-Sectional Study of Student Use and Perceptions in New Zealand.

AIMS: To investigate the usage, implications, and perceptions of ChatGPT among dental students and understand how students incorporate ChatGPT into th...

Zero-TE MRI-based attenuation correction for bone components on chest [18F] FDG PET/MRI: accuracy, repeatability, and external validation of an unsupervised deep learning approach using unpaired PET/CT data.

OBJECTIVE: In positron emission tomography (PET)/magnetic resonance imaging (MRI), attenuation correction (AC) for PET of the head is achieved by MRI ...

Comparative analysis of large language models and clinicians in thyroid eye disease using structured questionnaires.

To preliminarily evaluate agreement between large language models (LLMs) and ophthalmic clinicians regarding thyroid eye disease (TED) clinical decisi...

Are Psychiatry Faculty Prepared to Guide AI Use? A National Survey.

OBJECTIVE: To assess psychiatry faculty knowledge, use, and perceptions of artificial intelligence (AI) in undergraduate medical education (UME) and g...

Identifying factors influencing acceptance of artificial intelligence among general practitioners in Danish general practice: a cross-sectional web-based survey study.

BACKGROUND: Despite rapid advances in artificial intelligence (AI), its adoption in Danish general practice remains limited and decentralized, relying...

MonoUNet: A Robust Tiny Neural Network for Automated Knee Cartilage Segmentation on Point-of-care Ultrasound Devices.

OBJECTIVE: To develop a robust and compact deep learning model for automated knee cartilage segmentation on point-of-care ultrasound (POCUS) devices. ...

Advances in the Identification and Agreement About Meta-Therapy for Voice Disorders: A Methodological Paper.

BACKGROUND: Meta-therapy (MT) is a powerful dialogue-based element of voice therapy that scaffolds patients' cognitive models of treatment. MT dialogu...

Interpretable Semantic Medical Image Segmentation with Style and Confidence.

The scarcity of semantically labelled data presents major challenges for medical image segmentation using deep learning models, and the "black-box" na...

Cognitive Function Assessment Using a Virtual Reality Serious Game System in Patients With Stable Schizophrenia: Prospective Cohort Study.

BACKGROUND: Cognitive impairment is a core and enduring deficit in schizophrenia, severely affecting social functioning and quality of life. Tradition...

Reducing social biases in text-based emotion prediction using semantic blinding and semantic propagation graph neural networks.

This paper introduces the Semantic Propagation Graph Neural Network (SProp GNN), a machine learning emotion prediction (EP) architecture that relies e...

DC bias optimization in intelligent DCO-OFDM Li-Fi systems using hybrid machine learning with hardware validation.

The main goal of this paper is to determine the optimal DC bias value for DC-biased optical orthogonal frequency division multiplexing (DCO-OFDM)- bas...

Diagnostic accuracy of artificial intelligence versus 263 pediatric clinicians for childhood exanthems.

Pediatric exanthematous diseases pose diagnostic challenges because clinical presentations overlap. To determine whether current artificial intelligen...

Machine learning and SHAP interpretation to identify high-level compassion fatigue among operating room nurses: a multicenter cross-sectional study.

BACKGROUND: Operating room nurses (ORNs) are at high risk for compassion fatigue (CF), which significantly impairs individuals' well-being, undermines...

Screening for diabetes mellitus in the US population using neural network-based modeling and complex survey designs.

Complex survey designs are widely used in medical cohort studies. Developing risk score models that adequately account for the sampling design is esse...

The MR quality landscape in Europe.

OBJECTIVES: Over the last few years, with the introduction of advanced MR imaging techniques, increasing exam demand and the growth of multi-center cl...