Surveys

The actual performance of ML/AI models in predicting radiation-induced toxicity in head and neck cancer: a systematic review and meta-analysis.

An increasing number of Artificial intelligence (AI) and machine learning (ML) models are being developed to predict radiation-induced toxicities (RITs) in patients with head and neck cancer (HNC). But their performance and reliability remain uncertain. This systematic review and meta-analysis evaluated the predictive accuracy and methodological quality of these models. We comprehensively searched...

Deep learning-based assessment of paraspinal muscle degeneration and its relationships to muscle function and disability outcomes in chronic low back pain: a prospective study.

OBJECTIVES: To investigate deep-learning (DL) model accuracy in quantifying multifidus (MF) and erector spinae (ES) fat fraction (FF) compared to Dixon MRI, and to explore the indirect effect of muscle function between muscle degeneration and disability outcomes in chronic low back pain (CLBP). MATERIALS AND METHODS: 96 CLBP and 86 healthy participants underwent 3 T MRI, muscle function assessment...

Evaluating the Reliability of GPT-4o in Histological Image Interpretation.

Advanced large language models with multimodal capabilities offer potential new applications in medical education. This study evaluated GPT-4o's perfo...

Acceptability of Using Artificial Intelligence in the National Health Service Breast Screening Program: A Randomized Online Survey of Screening-Eligible Women in England.

OBJECTIVE: To compare acceptability of 2 artificial intelligence (AI) use cases in the English National Health Servic Breast Screening Program. PATIEN...

Leveraging low-cost app-based step count data to assess depression and anxiety in university students: A cross-sectional mobile health study.

BACKGROUND: The prevalence of depression and anxiety among college students worldwide is on the rise, significantly impacting their health and quality...

Literature-informed ensemble machine learning for three-year diabetic kidney disease risk prediction in type 2 diabetes: Development, validation, and deployment of the PSMMC NephraRisk model.

INTRODUCTION: Diabetic kidney disease (DKD) and diabetic nephropathy (DN) affect around 40% of diabetic patients but lack accurate risk prediction too...

Clinical practice, barriers to implementation, and priorities for equitable access of Stereotactic Body Radiation Therapy: An analysis of the global status by the ESTRO SBRT Focus Group.

BACKGROUND: Stereotactic Body Radiation Therapy (SBRT) has become an established treatment for several primary and metastatic malignancies; however, c...

mModPoEs: Multimodal posture estimation and feedback-driven correction of load-bearing human movements using wearable sensors and computer vision.

OBJECTIVE: Improper spinal posture during activities of daily living such as seated posture, upright stance, and ambulation, particularly under load-b...

Clinical validation of fully automated (peri-)articular tissue analysis for assessing osteoarthritis progression: A narrative review.

Numerous studies have presented fully automated techniques for assessing structural osteoarthritis (OA) progression, with recent work increasingly rel...

Performance of ChatGPT versus spine surgeons as an emergency department spine call consultant.

BACKGROUND: Large language models (LLMs) like ChatGPT are increasingly being recognized as credible tools for use across diverse healthcare settings. ...

Exploring the impact of AI technostress on physicians' job insecurity and performance from an empirical multi-hospital study.

This study expands Califf's technostress model, which explores the psychological stress caused by technology, by integrating "perceived self-esteem th...

Using, misusing, and improving online machine learning-based meta-analysis of neuroimaging published data: A perspective on NeuroQuery.

Online, text-based meta-analysis tools for large databases represent a new digital advance for medical, health, and neuroscience research, among other...

Deep Learning in Vertebral Fracture Detection: Systematic Review and Meta-analysis of Subject- vs. Vertebra-Level Approaches.

RATIONALE AND OBJECTIVES: To provide a context-aware evaluation of deep learning algorithms for vertebral fracture detection by disentangling subject-...

Validation of an artificial intelligence program in the characterization of breast nodules by ultrasound.

INTRODUCTION: Breast ultrasound is a widely accessible imaging method but highly operator-dependent. Artificial intelligence (AI) may improve breast l...

Enhancing Asleep Deep Brain Stimulation Targeting for Essential Tremor Using Machine Learning: The OPTIVIM Phase 2 Study.

BACKGROUND AND OBJECTIVES: Deep brain stimulation (DBS) is an effective treatment of essential tremor, but the optimal target and how to reach it with...

Development and validation of a novel machine learning-based algorithm to predict incident atrial fibrillation: A multicohort analysis.

BACKGROUND: Existing atrial fibrillation (AF) risk prediction models incorporate race as a covariate, systematically underestimating AF risk in black ...

LAT-BirdDrone: A dedicated dataset for high-precision classification of low-altitude small target trajectories enhanced by hybrid neural networks.

Currently, most existing datasets predominantly focus on object classification based on appearance, while datasets specifically designed for trajector...

Evaluation and improvement of algorithmic fairness for COVID-19 severity classification using Explainable Artificial Intelligence-based bias mitigation.

OBJECTIVES: The COVID-19 pandemic has highlighted the growing reliance on machine learning (ML) models for predicting disease severity, which is impor...

Content validity of AI-generated stuttering assessment and intervention programs based on expert review: A comparative analysis across age groups and language versions.

PURPOSE: This study aimed to evaluate the content validity and inter-rater reliability of stuttering assessment and intervention programs generated by...

Assessment of Artificial Intelligence (AI)-Powered Self-Care Recommendations for Management of Minor Ailments: A Comparative Analysis.

INTRODUCTION: Self-care and self-medication are increasingly viewed as helpful approaches to managing minor ailments; however, patients are often not ...