AIMC Topic: Reproducibility of Results

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Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis.

BMC cardiovascular disorders Apr 7, 2025
BACKGROUND: Heart failure (HF) impacts nearly 6 million individuals in the U.S., with a projected 46% increase by 2030, is creating significant healthcare burdens. Predictive models, particularly machine learning (ML)-based models, offer promising so...
Humans Predictive Value of Tests Heart Failure Patient Readmission Aged Machine Learning Female Male Decision Support Techniques Reproducibility of Results Risk Assessment Prognosis Risk Factors
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ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning.

BMC cardiovascular disorders Apr 7, 2025
A heart arrhythmia refers to a set of conditions characterized by irregular heart- beats, with an increasing mortality rate in recent years. Regular monitoring is essential for effective management, as early detection and timely treatment greatly imp...
Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Arrhythmias, Cardiac Heart Rate Reproducibility of Results Diagnosis, Computer-Assisted Electrocardiography Humans Machine Learning Algorithms
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Predator crow search optimization with explainable AI for cardiac vascular disease classification.

Scientific reports Apr 5, 2025
The proposed framework optimizes Explainable AI parameters, combining Predator crow search optimization to refine the predictive model's performance. To prevent overfitting and enhance feature selection, an information acquisition-based technique is ...
Cardiovascular Diseases Artificial Intelligence Algorithms Reproducibility of Results Humans
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Scale selection and machine learning based cell segmentation and tracking in time lapse microscopy.

Scientific reports Apr 5, 2025
Monitoring and tracking of cell motion is a key component for understanding disease mechanisms and evaluating the effects of treatments. Time-lapse optical microscopy has been commonly employed for studying cell cycle phases. However, usual manual ce...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Cell Movement Microscopy Machine Learning Algorithms Reproducibility of Results Cell Tracking Time-Lapse Imaging
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Deep learning-based uncertainty quantification for quality assurance in hepatobiliary imaging-based techniques.

Oncotarget Apr 4, 2025
Recent advances in deep learning models have transformed medical imaging analysis, particularly in radiology. This editorial outlines how uncertainty quantification through embedding-based approaches enhances diagnostic accuracy and reliability in he...
Diagnostic Imaging Quality Assurance, Health Care Uncertainty Reproducibility of Results Deep Learning Liver Neoplasms Humans
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Towards clinical implementation of automated segmentation of vestibular schwannomas: a reliability study comparing AI and human performance.

Neuroradiology Apr 4, 2025
PURPOSE: To evaluate the clinimetric reliability of automated vestibular schwannoma (VS) segmentations by a comparison with human inter-observer variability on T1-weighted contrast-enhanced MRI scans.
Adult Male Middle Aged Humans Female Artificial Intelligence Reproducibility of Results Retrospective Studies Image Interpretation, Computer-Assisted Aged Contrast Media Observer Variation Magnetic Resonance Imaging Neuroma, Acoustic Tumor Burden
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Identification and validation of HOXC6 as a diagnostic biomarker for Ewing sarcoma: insights from machine learning algorithms and experiments.

Frontiers in immunology Apr 4, 2025
INTRODUCTION: Early diagnosis of Ewing sarcoma (ES) is critical for improving patient prognosis. However, the accurate diagnosis of ES remains challenging, underscoring the need for novel diagnostic biomarkers to enhance diagnostic precision and reli...
Cell Proliferation Cell Movement Bone Neoplasms Homeodomain Proteins Sarcoma, Ewing Gene Expression Profiling Humans Cell Line, Tumor Gene Expression Regulation, Neoplastic Machine Learning Reproducibility of Results Biomarkers, Tumor
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Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm.

Scientific reports Apr 3, 2025
In the era of rapid digital communication, vast amounts of textual data are generated daily, demanding efficient methods for latent content analysis to extract meaningful insights. Large Language Models (LLMs) offer potential for automating this proc...
Politics Humans Language Reproducibility of Results Emotions Large Language Models
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Evaluation of correctness and reliability of GPT, Bard, and Bing chatbots' responses in basic life support scenarios.

Scientific reports Apr 3, 2025
Timely recognition and initiation of basic life support (BLS) before emergency medical services arrive significantly improve survival rates and neurological outcomes. In an era where health information-seeking behaviors have shifted toward online sou...
Female Reproducibility of Results Adult Humans Artificial Intelligence Generative Artificial Intelligence Cross-Sectional Studies Emergency Medical Services Male Infant
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AI Chatbots as Sources of STD Information: A Study on Reliability and Readability.

Journal of medical systems Apr 3, 2025
BACKGROUND: Artificial intelligence (AI) chatbots are increasingly used for medical inquiries, including sensitive topics like sexually transmitted diseases (STDs). However, concerns remain regarding the reliability and readability of the information...
Health Literacy Generative Artificial Intelligence Sexually Transmitted Diseases Humans Comprehension Artificial Intelligence Reproducibility of Results
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