AIMC Topic: Female

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Directed EEG neural network analysis by LAPPS (p≤1) Penalized sparse Granger approach.

Neural networks : the official journal of the International Neural Network Society Jan 25, 2020
The conventional multivariate Granger Analysis (GA) of directed interactions has been widely applied in brain network construction based on EEG recordings as well as fMRI. Nevertheless, EEG is usually inevitably contaminated by strong noise, which ma...
Motor Cortex Humans Neural Networks, Computer Female Male Electroencephalography
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Automated classification of normal and Stargardt disease optical coherence tomography images using deep learning.

Acta ophthalmologica Jan 24, 2020
PURPOSE: Recent advances in deep learning have seen an increase in its application to automated image analysis in ophthalmology for conditions with a high prevalence. We wanted to identify whether deep learning could be used for the automated classif...
Image Processing, Computer-Assisted Tomography, Optical Coherence Stargardt Disease Humans Female Middle Aged Adult Severity of Illness Index Male Case-Control Studies Deep Learning ROC Curve
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Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.

Esophagus : official journal of the Japan Esophageal Society Jan 24, 2020
OBJECTIVES: In Japan, endoscopic resection (ER) is often used to treat esophageal squamous cell carcinoma (ESCC) when invasion depths are diagnosed as EP-SM1, whereas ESCC cases deeper than SM2 are treated by surgical operation or chemoradiotherapy. ...
Outcome Assessment, Health Care Esophageal Squamous Cell Carcinoma Preoperative Care Endoscopic Mucosal Resection Neoplasm Invasiveness Area Under Curve Esophageal Neoplasms Japan Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Sensitivity and Specificity Male Middle Aged Deep Learning Humans Neural Networks, Computer Artificial Intelligence
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A Comparative Classification Analysis of Abdominal Aortic Aneurysms by Machine Learning Algorithms.

Annals of biomedical engineering Jan 24, 2020
The objective of this work was to perform image-based classification of abdominal aortic aneurysms (AAA) based on their demographic, geometric, and biomechanical attributes. We retrospectively reviewed existing demographics and abdominal computed tom...
Aneurysm, Ruptured Middle Aged Aortic Aneurysm, Abdominal Computed Tomography Angiography Finite Element Analysis Humans Machine Learning Female Aged Aged, 80 and over Male
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Machine learning validation of EEG+tACS artefact removal.

Journal of neural engineering Jan 24, 2020
OBJECTIVE: Electroencephalography (EEG) recorded during transcranial alternating current simulation (tACS) is highly desirable in order to investigate brain dynamics during stimulation, but is corrupted by large amplitude stimulation artefacts. Artef...
Humans Machine Learning Female Reproducibility of Results Young Adult Psychomotor Performance Adult Artifacts Male Random Allocation Electroencephalography Photic Stimulation Memory, Short-Term Transcranial Direct Current Stimulation
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Design of a deep learning model for automatic scoring of periodic and non-periodic leg movements during sleep validated against multiple human experts.

Sleep medicine Jan 23, 2020
OBJECTIVE: Currently, manual scoring is the gold standard of leg movement scoring (LMs) and periodic LMs (PLMS) in overnight polysomnography (PSG) studies, which is subject to inter-scorer variability. The objective of this study is to design and val...
Electromyography Humans Male Sleep Algorithms Middle Aged Deep Learning Polysomnography Female Cohort Studies Nocturnal Myoclonus Syndrome Adult
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Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.

International journal of radiation oncology, biology, physics Jan 23, 2020
PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes ass...
Aged, 80 and over Adult Breast Neoplasms Middle Aged Skin Supervised Machine Learning Molecular Imaging Skin Temperature Radiodermatitis Humans Biomarkers Female Aged
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Coronary Artery Disease Diagnosis; Ranking the Significant Features Using a Random Trees Model.

International journal of environmental research and public health Jan 23, 2020
Heart disease is one of the most common diseases in middle-aged citizens. Among the vast number of heart diseases, coronary artery disease (CAD) is considered as a common cardiovascular disease with a high death rate. The most popular tool for diagno...
Humans Male Middle Aged Diagnosis, Computer-Assisted Support Vector Machine Decision Trees Female Aged Aged, 80 and over Adult Coronary Artery Disease
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A Novel Deep Learning Approach with a 3D Convolutional Ladder Network for Differential Diagnosis of Idiopathic Normal Pressure Hydrocephalus and Alzheimer's Disease.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Jan 22, 2020
PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) and Alzheimer's disease (AD) are geriatric diseases and common causes of dementia. Recently, many studies on the segmentation, disease detection, or classification of MRI using deep learning ha...
Alzheimer Disease Pattern Recognition, Automated Neuroimaging Hydrocephalus, Normal Pressure Middle Aged Disease Progression Case-Control Studies Diagnosis, Computer-Assisted Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted Female Magnetic Resonance Imaging Reproducibility of Results Humans Diagnosis, Differential Aged Artificial Intelligence Aged, 80 and over Brain Male
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Automated body composition analysis of clinically acquired computed tomography scans using neural networks.

Clinical nutrition (Edinburgh, Scotland) Jan 22, 2020
BACKGROUND & AIMS: The quantity and quality of skeletal muscle and adipose tissue is an important prognostic factor for clinical outcomes across several illnesses. Clinically acquired computed tomography (CT) scans are commonly used for quantificatio...
Lumbar Vertebrae Female Adiposity Automation Reproducibility of Results North America Aged Adult Male Humans Muscle, Skeletal Neural Networks, Computer Tomography, X-Ray Computed Middle Aged Adipose Tissue Deep Learning Predictive Value of Tests Europe Body Composition Sarcopenia Radiographic Image Interpretation, Computer-Assisted
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