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Reproducibility of Results

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Applying support vector machines to a diagnostic classification model for polytomous attributes in small-sample contexts.

The British journal of mathematical and statistical psychology
Over several years, the evaluation of polytomous attributes in small-sample settings has posed a challenge to the application of cognitive diagnosis models. To enhance classification precision, the support vector machine (SVM) was introduced for esti...

Detection of Low Resilience Using Data-Driven Effective Connectivity Measures.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Conventional thresholding techniques for graph theory analysis, such as absolute, proportional and mean degree, have often been used in characterizing human brain networks under different mental disorders, such as mental stress. However, these approa...

Deep learning segmentation model for quantification of infarct size in pigs with myocardial ischemia/reperfusion.

Basic research in cardiology
Infarct size (IS) is the most robust end point for evaluating the success of preclinical studies on cardioprotection. The gold standard for IS quantification in ischemia/reperfusion (I/R) experiments is triphenyl tetrazolium chloride (TTC) staining, ...

Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o.

Clinical rheumatology
OBJECTIVES: This study evaluates the performance of AI models, ChatGPT-4o and Google Gemini, in answering rheumatology board-level questions, comparing their effectiveness, reliability, and applicability in clinical practice.

Comparison of semi and fully automated artificial intelligence driven softwares and manual system for cephalometric analysis.

BMC medical informatics and decision making
BACKGROUND: Cephalometric analysis has been used as one of the main tools for orthodontic diagnosis and treatment planning. The analysis can be performed manually on acetate tracing sheets, digitally by manual selection of landmarks or by recently in...

Predicting diabetes in adults: identifying important features in unbalanced data over a 5-year cohort study using machine learning algorithm.

BMC medical research methodology
BACKGROUND: Imbalanced datasets pose significant challenges in predictive modeling, leading to biased outcomes and reduced model reliability. This study addresses data imbalance in diabetes prediction using machine learning techniques. Utilizing data...

Recurrent Neural Network Enabled Continuous Motion Estimation of Lower Limb Joints From Incomplete sEMG Signals.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Decoding continuous human motion from surface electromyography (sEMG) in advance is crucial for improving the intelligence of exoskeleton robots. However, incomplete sEMG signals are prevalent on account of unstable data transmission, sensor malfunct...

Implementation of machine learning models as a quantitative evaluation tool for preclinical studies in dental education.

Journal of dental education
PURPOSE AND OBJECTIVE: Objective, valid, and reliable evaluations are needed in order to develop haptic skills in dental education. The aim of this study is to investigate the validity and reliability of the machine learning method in evaluating the ...

Are automated video interviews smart enough? Behavioral modes, reliability, validity, and bias of machine learning cognitive ability assessments.

The Journal of applied psychology
Automated video interviews (AVIs) that use machine learning (ML) algorithms to assess interviewees are increasingly popular. Extending prior AVI research focusing on noncognitive constructs, the present study critically evaluates the possibility of a...

Evaluating the accuracy and reliability of AI chatbots in disseminating the content of current resuscitation guidelines: a comparative analysis between the ERC 2021 guidelines and both ChatGPTs 3.5 and 4.

Scandinavian journal of trauma, resuscitation and emergency medicine
AIM OF THE STUDY: Artificial intelligence (AI) chatbots are established as tools for answering medical questions worldwide. Healthcare trainees are increasingly using this cutting-edge technology, although its reliability and accuracy in the context ...