AIMC Topic: Reproducibility of Results

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Deep Learning Model of Diastolic Dysfunction Risk Stratifies the Progression of Early-Stage Aortic Stenosis.

JACC. Cardiovascular imaging Sep 18, 2024
BACKGROUND: The development and progression of aortic stenosis (AS) from aortic valve (AV) sclerosis is highly variable and difficult to predict.
United States Calcinosis Aortic Valve Stenosis Aortic Valve Predictive Value of Tests Disease Progression Severity of Illness Index Deep Learning Time Factors Ventricular Dysfunction, Left Diastole Sclerosis Female Reproducibility of Results Risk Factors Aged Male Ventricular Function, Left Echocardiography Middle Aged Risk Assessment Humans Prognosis
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Automatic Feature Selection for Sensorimotor Rhythms Brain-Computer Interface Fusing Expert and Data-Driven Knowledge.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 18, 2024
Early brain-computer interface (BCI) systems were mainly based on prior neurophysiological knowledge coupled with feedback training, while state-of-the-art interfaces rely on data-driven, machine learning (ML)-oriented methods. Despite the advances i...
Fuzzy Logic Electroencephalography Brain-Computer Interfaces Imagination Machine Learning Algorithms Reproducibility of Results Adult Humans
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Deep Learning Model for Pathological Grading and Prognostic Assessment of Lung Cancer Using CT Imaging: A Study on NLST and External Validation Cohorts.

Academic radiology Sep 17, 2024
RATIONALE AND OBJECTIVES: To develop and validate a deep learning model for automated pathological grading and prognostic assessment of lung cancer using CT imaging, thereby providing surgeons with a non-invasive tool to guide surgical planning.
Lung Neoplasms Tomography, X-Ray Computed Carcinoma, Non-Small-Cell Lung Female Reproducibility of Results Neoplasm Grading Aged Sensitivity and Specificity Male Humans Middle Aged Prognosis Deep Learning Cohort Studies
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Insights Into Detecting Adult ADHD Symptoms Through Advanced Dual-Stream Machine Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 17, 2024
Advancements in machine learning offer promising avenues for the identification of ADHD symptoms in adults, an endeavour traditionally encumbered by the intricacies of human behavioural patterns. In this paper, we introduce three innovative dual-stre...
Humans Video Recording Attention Deficit Disorder with Hyperactivity Young Adult Adult Male Machine Learning Posture Algorithms Hand Female Reproducibility of Results
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Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 17, 2024
The objective of this work is to develop a novel myoelectric pattern recognition (MPR) method to mitigate the concurrent interference of electrode shift and loosening, thereby improving the practicality of MPR-based gestural interfaces towards intell...
Electrodes Pattern Recognition, Automated Male Gestures Support Vector Machine Electromyography Humans Neural Networks, Computer Algorithms Female Reproducibility of Results Young Adult Adult
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Advancements in opportunistic intracranial aneurysm screening: The impact of a deep learning algorithm on radiologists' analysis of T2-weighted cranial MRI.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Sep 16, 2024
(1) Background: Unruptured Intracranial Aneurysms (UIAs) are common blood vessel malformations, occurring in up to 3 % of healthy adults. Magnetic Resonance Angiography (MRA) is frequently used for the screening of UIAs due to its high resolution in ...
Female Reproducibility of Results Aged Adult Male Humans Middle Aged Radiologists Deep Learning Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Observer Variation Predictive Value of Tests Magnetic Resonance Angiography Intracranial Aneurysm
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Automated classification of Alzheimer's disease, mild cognitive impairment, and cognitively normal patients using 3D convolutional neural network and radiomic features from T1-weighted brain MRI: A comparative study on detection accuracy.

Clinical imaging Sep 16, 2024
OBJECTIVES: Alzheimer's disease (AD) is a common neurodegenerative disorder that primarily affects older individuals. Due to its high incidence, an accurate and efficient stratification system could greatly aid in the clinical diagnosis and prognosis...
Neural Networks, Computer Algorithms Brain Female Reproducibility of Results Humans Cognitive Dysfunction Magnetic Resonance Imaging Alzheimer Disease Aged Aged, 80 and over Radiomics Male
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Investigating artificial intelligence models for predicting joint pain from serum biochemistry.

Revista da Associacao Medica Brasileira (1992) Sep 16, 2024
OBJECTIVE: The study used machine learning models to predict the clinical outcome with various attributes or when the models chose features based on their algorithms.
Creatinine Arthralgia Aged Algorithms Young Adult Middle Aged Humans Adult Biomarkers Adolescent Neural Networks, Computer Male Female Artificial Intelligence Predictive Value of Tests Reproducibility of Results Machine Learning C-Reactive Protein Uric Acid
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A Learnable and Explainable Wavelet Neural Network for EEG Artifacts Detection and Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 16, 2024
Electroencephalography (EEG) artifacts are very common in clinical diagnosis and can heavily impact diagnosis. Manual screening of artifact events is labor-intensive with little benefit. Therefore, exploring algorithms for automatic detection and cla...
Neural Networks, Computer Machine Learning Algorithms Reproducibility of Results Electroencephalography Signal Processing, Computer-Assisted Artifacts Wavelet Analysis Humans
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Clinical value of artificial intelligence 3D echocardiography in evaluating left atrial volume and pulmonary vein structure in patients with atrial fibrillation.

Clinics (Sao Paulo, Brazil) Sep 15, 2024
OBJECTIVE: To explore the clinical value of 3D Echocardiography (3DE) in evaluating the changes of left atrial volume and pulmonary vein structure in patients with Atrial Fibrillation (AF).
Female Reproducibility of Results Aged Adult Male Humans Artificial Intelligence Atrial Fibrillation Heart Atria Middle Aged Echocardiography, Three-Dimensional Case-Control Studies Pulmonary Veins Organ Size Reference Values
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