AIMC Topic: Reproducibility of Results
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Automated deep learning segmentation of cardiac inflammatory FDG PET.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Oct 3, 2024
BACKGROUND: Fluorodeoxyglucose positron emission tomography (FDG PET) with suppression of myocardial glucose utilization plays a pivotal role in diagnosing cardiac sarcoidosis. Reorientation of images to match perfusion datasets and myocardial segmen...
De Novo Natural Language Processing Algorithm Accurately Identifies Myxofibrosarcoma From Pathology Reports.
Clinical orthopaedics and related research
Oct 2, 2024
BACKGROUND: Available codes in the ICD-10 do not accurately reflect soft tissue sarcoma diagnoses, and this can result in an underrepresentation of soft tissue sarcoma in databases. The National VA Database provides a unique opportunity for soft tiss...
Accelerated 2D radial Look-Locker T1 mapping using a deep learning-based rapid inversion recovery sampling technique.
NMR in biomedicine
Oct 2, 2024
Efficient abdominal coverage with T1-mapping methods currently available in the clinic is limited by the breath hold period (BHP) and the time needed for T1 recovery. This work develops a T1-mapping framework for efficient abdominal coverage based on...
Developing and Validating a Multimodal Dataset for Neonatal Pain Assessment to Improve AI Algorithms With Clinical Data.
Advances in neonatal care : official journal of the National Association of Neonatal Nurses
Oct 2, 2024
BACKGROUND: Using Artificial Intelligence (AI) for neonatal pain assessment has great potential, but its effectiveness depends on accurate data labeling. Therefore, precise and reliable neonatal pain datasets are essential for managing neonatal pain.
Deep-Learning-Based Disease Classification in Patients Undergoing Cine Cardiac MRI.
Journal of magnetic resonance imaging : JMRI
Oct 1, 2024
BACKGROUND: Automated approaches may allow for fast, reproducible clinical assessment of cardiovascular diseases from MRI.
Male
Middle Aged
Humans
Deep Learning
Female
Image Processing, Computer-Assisted
Cardiomyopathy, Hypertrophic
Reproducibility of Results
Magnetic Resonance Imaging, Cine
Heart
Aged
Myocardial Ischemia
Algorithms
Heart Ventricles
Cardiomyopathy, Dilated
Adult
Retrospective Studies
Image Interpretation, Computer-Assisted
Sensitivity and Specificity
Applying support vector machines to a diagnostic classification model for polytomous attributes in small-sample contexts.
The British journal of mathematical and statistical psychology
Oct 1, 2024
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
Oct 1, 2024
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
Sep 30, 2024
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
Sep 28, 2024
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
Sep 27, 2024
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...
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