AIMC Topic: Reproducibility of Results
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Evaluating large language models as a supplementary patient information resource on antimalarial use in systemic lupus erythematosus.
Lupus
Feb 27, 2025
ObjectiveTo assess the accuracy, completeness, and reproducibility of Large Language Models (LLMs) (Copilot, GPT-3.5, and GPT-4) on antimalarial use in systemic lupus erythematosus (SLE).Materials and MethodsWe utilized 13 questions derived from pati...
Deep Learning for Ultrasonographic Assessment of Temporomandibular Joint Morphology.
Tomography (Ann Arbor, Mich.)
Feb 27, 2025
BACKGROUND: Temporomandibular joint (TMJ) disorders are a significant cause of orofacial pain. Artificial intelligence (AI) has been successfully applied to other imaging modalities but remains underexplored in ultrasonographic evaluations of TMJ.
Advancing Clinical Chatbot Validation Using AI-Powered Evaluation With a New 3-Bot Evaluation System: Instrument Validation Study.
JMIR nursing
Feb 27, 2025
BACKGROUND: The health care sector faces a projected shortfall of 10 million workers by 2030. Artificial intelligence (AI) automation in areas such as patient education and initial therapy screening presents a strategic response to mitigate this shor...
Investigation of Inter-Patient, Intra-Patient, and Patient-Specific Based Training in Deep Learning for Classification of Heartbeat Arrhythmia.
Cardiovascular engineering and technology
Feb 26, 2025
Effective diagnosis of electrocardiogram (ECG) is one of the simplest and fastest ways to assess the heart's function. In the recent decade, various attempts have been made to automate the classification of electrocardiogram signals to detect heartbe...
Post-Mortem imaging biobanks: Building data for reproducibility, standardization, and AI integration.
European journal of radiology
Feb 26, 2025
In recent years, post-mortem imaging has advanced with techniques such as Post-Mortem Computed Tomography (PMCT) and Post-Mortem Magnetic Resonance imaging (PMMR). PMCT is particularly useful for assessing skeletal injuries, vascular lesions, and est...
Enhanced glioma tumor detection and segmentation using modified deep learning with edge fusion and frequency features.
Scientific reports
Feb 26, 2025
Computer-aided automatic brain tumor detection is crucial for timely diagnosis and treatment, especially in regions with limited access to medical expertise. However, existing methods often overlook edge pixel information during tumor segmentation, l...
Impact of an artificial intelligence decision support system among radiologists with different levels of experience in breast ultrasound: A prospective study in a tertiary center.
European journal of radiology
Feb 25, 2025
PURPOSE: To assess the impact of an artificial intelligence decision support system (Koios DS) on the diagnostic performance of radiologists with different experience in breast ultrasound and to evaluate its potential to reduce unnecessary biopsies.
Quality assurance and validity of AI-generated single best answer questions.
BMC medical education
Feb 25, 2025
BACKGROUND: Recent advancements in generative artificial intelligence (AI) have opened new avenues in educational methodologies, particularly in medical education. This study seeks to assess whether generative AI might be useful in addressing the dep...
RAE-Net: a multi-modal neural network based on feature fusion and evidential deep learning algorithm in predicting breast cancer subtypes on DCE-MRI.
Biomedical physics & engineering express
Feb 25, 2025
Accurate identification of molecular subtypes in breast cancer is critical for personalized treatment. This study introduces a novel neural network model, RAE-Net, based on Multimodal Feature Fusion (MFF) and the Evidential Deep Learning Algorithm (E...
End-User Confidence in Artificial Intelligence-Based Predictions Applied to Biomedical Data.
International journal of neural systems
Feb 24, 2025
Applications of Artificial Intelligence (AI) are revolutionizing biomedical research and healthcare by offering data-driven predictions that assist in diagnoses. Supervised learning systems are trained on large datasets to predict outcomes for new te...
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