AIMC Topic: Middle 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...
Support Vector Machine Decision Trees Coronary Artery Disease Aged, 80 and over Adult Male Humans Middle Aged Female Diagnosis, Computer-Assisted Aged
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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...
Case-Control Studies Diagnosis, Computer-Assisted Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted Aged Aged, 80 and over Male Magnetic Resonance Imaging Middle Aged Diagnosis, Differential Disease Progression Alzheimer Disease Humans Pattern Recognition, Automated Artificial Intelligence Neuroimaging Brain Hydrocephalus, Normal Pressure Female Reproducibility of Results
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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...
Aged Body Composition Europe Humans Adult Radiographic Image Interpretation, Computer-Assisted Sarcopenia Male Neural Networks, Computer Muscle, Skeletal Lumbar Vertebrae Middle Aged Tomography, X-Ray Computed Adipose Tissue Adiposity Deep Learning Female Predictive Value of Tests Automation Reproducibility of Results North America
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Antioxidant and Anti-inflammatory Diagnostic Biomarkers in Multiple Sclerosis: A Machine Learning Study.

Molecular neurobiology Jan 22, 2020
An imbalance of inflammatory/anti-inflammatory and oxidant/antioxidant molecules has been implicated in the demyelination and axonal damage in multiple sclerosis (MS). The current study aimed to evaluate the plasma levels of tumor necrosis factor (TN...
Antioxidants Nitric Oxide Sulfhydryl Compounds Inflammation Female Humans Multiple Sclerosis Support Vector Machine Adult Neural Networks, Computer Adiponectin Oxidation-Reduction Sensitivity and Specificity Tumor Necrosis Factor-alpha Advanced Oxidation Protein Products Biomarkers Male Nitrosative Stress Middle Aged Receptors, Tumor Necrosis Factor Oxidative Stress
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Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

The lancet. Gastroenterology & hepatology Jan 22, 2020
BACKGROUND: Colonoscopy with computer-aided detection (CADe) has been shown in non-blinded trials to improve detection of colon polyps and adenomas by providing visual alarms during the procedure. We aimed to assess the effectiveness of a CADe system...
Middle Aged Observer Variation Humans Colonoscopy Incidence Female Early Diagnosis Case-Control Studies Mass Screening Adult Clinical Alarms Diagnosis, Computer-Assisted Adenoma Colorectal Neoplasms Deep Learning Double-Blind Method Male China Colonic Polyps
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Image Quality and Lesion Detection on Deep Learning Reconstruction and Iterative Reconstruction of Submillisievert Chest and Abdominal CT.

AJR. American journal of roentgenology Jan 22, 2020
The objective of this study was to compare image quality and clinically significant lesion detection on deep learning reconstruction (DLR) and iterative reconstruction (IR) images of submillisievert chest and abdominopelvic CT. Our prospective mult...
Male Middle Aged Deep Learning Imaging, Three-Dimensional Contrast Media Radiographic Image Interpretation, Computer-Assisted Humans Prospective Studies Tomography, X-Ray Computed Female Aged Radiation Dosage Radiography, Thoracic Radiography, Abdominal
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Acceptability of artificial intelligence (AI)-enabled chatbots, video consultations and live webchats as online platforms for sexual health advice.

BMJ sexual & reproductive health Jan 21, 2020
OBJECTIVES: Sexual and reproductive health (SRH) services are undergoing a digital transformation. This study explored the acceptability of three digital services, (i) video consultations via Skype, (ii) live webchats with a health advisor and (iii) ...
United Kingdom Patient Acceptance of Health Care Sexual Health Hotlines Reproductive Health Services Artificial Intelligence Male Female Humans Middle Aged Aged Surveys and Questionnaires Adult Adolescent Cross-Sectional Studies Logistic Models Internet
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Diagnostic performance of a deep learning convolutional neural network in the differentiation of combined naevi and melanomas.

Journal of the European Academy of Dermatology and Venereology : JEADV Jan 21, 2020
BACKGROUND: Deep learning convolutional neural networks (CNN) may assist physicians in the diagnosis of melanoma. The capacity of a CNN to differentiate melanomas from combined naevi, the latter representing well-known melanoma simulators, has not be...
Humans Female Melanoma Skin Neoplasms Dermoscopy Aged Diagnosis, Computer-Assisted Young Adult Deep Learning Adult Clinical Competence Sensitivity and Specificity Dermatologists Male Melanocytes Middle Aged Nevus, Pigmented
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The diagnostic value of quantitative texture analysis of conventional MRI sequences using artificial neural networks in grading gliomas.

Clinical radiology Jan 21, 2020
AIM: To explore the value of quantitative texture analysis of conventional magnetic resonance imaging (MRI) sequences using artificial neural networks (ANN) for the differentiation of high-grade gliomas (HGG) and low-grade gliomas (LGG).
Female Reproducibility of Results Aged Adult Brain Neoplasms Male Middle Aged Glioma Contrast Media Humans Magnetic Resonance Imaging Neural Networks, Computer Neoplasm Grading Image Interpretation, Computer-Assisted
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Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.

European radiology Jan 21, 2020
OBJECTIVES: To propose a transfer learning (TL) radiomics model that efficiently combines the information from gray scale and elastogram ultrasound images for accurate liver fibrosis grading.
Machine Learning Algorithms Biomarkers Retrospective Studies Female Aged Humans Neural Networks, Computer Liver Area Under Curve Hepatitis B, Chronic Data Accuracy Elasticity Imaging Techniques Adult Male Middle Aged ROC Curve Liver Cirrhosis
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