AIMC Topic:
Young Adult
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Multicenter Validation of a Deep Learning Detection Algorithm for Focal Cortical Dysplasia.
Neurology
Sep 14, 2021
BACKGROUND AND OBJECTIVE: To test the hypothesis that a multicenter-validated computer deep learning algorithm detects MRI-negative focal cortical dysplasia (FCD).
Pre-surgical and Post-surgical Aortic Aneurysm Maximum Diameter Measurement: Full Automation by Artificial Intelligence.
European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
Sep 10, 2021
OBJECTIVE: The aim of this study was to evaluate an automatic, deep learning based method (Augmented Radiology for Vascular Aneurysm [ARVA]), to detect and assess maximum aortic diameter, providing cross sectional outer to outer aortic wall measureme...
Automation
Computed Tomography Angiography
Young Adult
Aortography
Adult
Male
Middle Aged
Retrospective Studies
Deep Learning
Female
Treatment Outcome
Humans
Reproducibility of Results
Predictive Value of Tests
Neural Networks, Computer
Aortic Aneurysm, Abdominal
Aged
Databases, Factual
Aged, 80 and over
Radiographic Image Interpretation, Computer-Assisted
Automated machine learning for endemic active tuberculosis prediction from multiplex serological data.
Scientific reports
Sep 9, 2021
Serological diagnosis of active tuberculosis (TB) is enhanced by detection of multiple antibodies due to variable immune responses among patients. Clinical interpretation of these complex datasets requires development of suitable algorithms, a time c...
Artificial neural network for the prediction model of glomerular filtration rate to estimate the normal or abnormal stages of kidney using gamma camera.
Annals of nuclear medicine
Sep 7, 2021
OBJECTIVE: Chronic kidney disease (CKD) is evaluated based on glomerular filtration rate (GFR) using a gamma camera in the nuclear medicine center or hospital in a routine procedure, but the gamma camera does not provide the accurate stages of the di...
MRI-Based Machine Learning Prediction Framework to Lateralize Hippocampal Sclerosis in Patients With Temporal Lobe Epilepsy.
Neurology
Sep 2, 2021
BACKGROUND AND OBJECTIVES: MRI fails to reveal hippocampal pathology in 30% to 50% of temporal lobe epilepsy (TLE) surgical candidates. To address this clinical challenge, we developed an automated MRI-based classifier that lateralizes the side of co...
Efficacy of a comprehensive binary classification model using a deep convolutional neural network for wireless capsule endoscopy.
Scientific reports
Sep 1, 2021
The manual reading of capsule endoscopy (CE) videos in small bowel disease diagnosis is time-intensive. Algorithms introduced to automate this process are premature for real clinical applications, and multi-diagnosis using these methods has not been ...
HOX cluster and their cofactors showed an altered expression pattern in eutopic and ectopic endometriosis tissues.
Reproductive biology and endocrinology : RB&E
Sep 1, 2021
Endometriosis is major gynecological disease that affects over 10% of women worldwide and 30%-50% of these women have pelvic pain, abnormal uterine bleeding and infertility. The cause of endometriosis is unknown and there is no definite cure mainly b...
Generative Adversarial Networks-Based Data Augmentation for Brain-Computer Interface.
IEEE transactions on neural networks and learning systems
Aug 31, 2021
The performance of a classifier in a brain-computer interface (BCI) system is highly dependent on the quality and quantity of training data. Typically, the training data are collected in a laboratory where the users perform tasks in a controlled envi...
Machine learning models of ischemia/hemorrhage in moyamoya disease and analysis of its risk factors.
Clinical neurology and neurosurgery
Aug 30, 2021
OBJECT: This study aimed to determine the risk factors of ischemic/hemorrhagic stroke in patients suffering moyamoya disease (MMD), as well as to compare the effects of six analysis methods.
Reducing the energy cost of running using a lightweight, low-profile elastic exosuit.
Journal of neuroengineering and rehabilitation
Aug 30, 2021
BACKGROUND: Human beings can enhance their distance running performance with the help of assistive devices. Although several such devices are available, they are heavy and bulky, which limits their use in everyday activities. In this study, we develo...
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