AIMC Topic: Diagnosis, Computer-Assisted

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A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data.

Computer methods and programs in biomedicine Oct 5, 2018
BACKGROUND AND OBJECTIVE: Cancer has become a complex health problem due to its high mortality. Over the past few decades, with the rapid development of the high-throughput sequencing technology and the application of various machine learning methods...
Pattern Recognition, Automated False Positive Reactions Breast Neoplasms Male Diagnosis, Computer-Assisted Deep Learning Gene Expression Regulation, Neoplastic Supervised Machine Learning RNA Lung Neoplasms Sequence Analysis, RNA Algorithms Female Reproducibility of Results Stomach Neoplasms Humans Software
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3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas.

Cancer research Oct 2, 2018
: Identification of early-stage pulmonary adenocarcinomas before surgery, especially in cases of subcentimeter cancers, would be clinically important and could provide guidance to clinical decision making. In this study, we developed a deep learning ...
Adult Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Female Aged Aged, 80 and over Young Adult Adenocarcinoma Neoplasm Invasiveness Decision Making Area Under Curve Mutation Adolescent Imaging, Three-Dimensional Image Processing, Computer-Assisted Lung Neoplasms Humans Prognosis Retrospective Studies Tomography, X-Ray Computed Neural Networks, Computer Precision Medicine
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Alzheimer's disease diagnosis based on multiple cluster dense convolutional networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Oct 2, 2018
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and cognitive functions. Structural magnetic resonance images (MRI) play important role to evaluate the brain anatomical changes for AD Diagn...
Algorithms Diagnosis, Computer-Assisted Alzheimer Disease Humans Neural Networks, Computer
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Diagnosis of urinary tract infection based on artificial intelligence methods.

Computer methods and programs in biomedicine Oct 2, 2018
BACKGROUND AND OBJECTIVE: Urinary tract infection (UTI) is a common disease affecting the vast majority of people. UTI involves a simple infection caused by urinary tract inflammation as well as a complicated infection that may be caused by an inflam...
Artificial Intelligence Machine Learning Algorithms Female Aged Humans Neural Networks, Computer Middle Aged Diagnosis, Computer-Assisted Adolescent Child ROC Curve Young Adult Adult Sensitivity and Specificity Male False Positive Reactions Cystitis Decision Support Systems, Clinical Support Vector Machine Decision Trees Urinary Tract Infections
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Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video).

Gastrointestinal endoscopy Sep 27, 2018
BACKGROUND AND AIMS: In the treatment of ulcerative colitis (UC), an incremental benefit of achieving histologic healing beyond that of endoscopic mucosal healing has been suggested; persistent histologic inflammation increases the risk of exacerbati...
Rectum Algorithms Diagnosis, Computer-Assisted Automation Retrospective Studies Inflammation Sensitivity and Specificity Middle Aged Female Colitis, Ulcerative Humans Male Colon Intestinal Mucosa Reproducibility of Results Artificial Intelligence Machine Learning Colonoscopy
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An SVM approach for identifying atrial fibrillation.

Physiological measurement Sep 27, 2018
OBJECTIVES: We designed an automated algorithm to classify short electrocardiogram (ECG) strips into four categories: normal rhythm, atrial fibrillation, noisy segment, or other rhythm disturbances.
Humans Electrocardiography Diagnosis, Computer-Assisted Support Vector Machine Atrial Fibrillation Pattern Recognition, Automated
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Multi-dimensional proprio-proximus machine learning for assessment of myocardial infarction.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 26, 2018
This work presents a novel analysis methodology that utilises high-resolution, multi-dimensional information to better classify regions of the left ventricle after myocardial infarction. Specifically, the focus is to determine degree of infarction in...
Pattern Recognition, Automated Machine Learning Diagnosis, Computer-Assisted Myocardial Infarction Heart Ventricles
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Automatic glomerular identification and quantification of histological phenotypes using image analysis and machine learning.

American journal of physiology. Renal physiology Sep 26, 2018
Current methods of scoring histological kidney samples, specifically glomeruli, do not allow for collection of quantitative data in a high-throughput and consistent manner. Neither untrained individuals nor computers are presently capable of identify...
Animals Male Diagnosis, Computer-Assisted Rats Kidney Diseases Predictive Value of Tests Biopsy Disease Models, Animal Mice, Inbred C57BL Automation, Laboratory Humans Workflow Phenotype Pattern Recognition, Automated Mice, Transgenic Female Machine Learning Kidney Glomerulus Species Specificity Reproducibility of Results Software Microscopy Image Interpretation, Computer-Assisted
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Aiding the Digital Mammogram for Detecting the Breast Cancer Using Shearlet Transform and Neural Network.

Asian Pacific journal of cancer prevention : APJCP Sep 26, 2018
Objective: Breast Cancer is the most invasive disease and fatal disease next to lung cancer in human. Early detection of breast cancer is accomplished by X-ray mammography. Mammography is the most effective and efficient technique used for detection ...
Wavelet Analysis Humans Breast Neoplasms Neural Networks, Computer Diagnosis, Computer-Assisted Algorithms Mammography Image Interpretation, Computer-Assisted Databases, Factual Image Enhancement Female Diagnostic Errors
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ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network.

Physiological measurement Sep 24, 2018
OBJECTIVE: The electrocardiogram (ECG) provides an effective, non-invasive approach for clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the most common cardiac rhythm disturbance and affects ~2% of the gen...
Arrhythmias, Cardiac Sensitivity and Specificity Diagnosis, Computer-Assisted Pattern Recognition, Automated Electrocardiography Humans Neural Networks, Computer
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