AIMC Topic: Diagnosis, Computer-Assisted

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Computer-aided system for diagnosing thyroid nodules on ultrasound: A comparison with radiologist-based clinical assessments.

Head & neck Dec 29, 2017
BACKGROUND: The purpose of this study was to compare the diagnostic efficiency of a thyroid ultrasound computer-aided diagnosis (CAD) system with that of 1 radiologist.
Retrospective Studies Female Adult Sensitivity and Specificity Male Middle Aged Diagnosis, Computer-Assisted China Humans Image-Guided Biopsy ROC Curve Ultrasonography, Interventional Radiologists Hospitals, University Cohort Studies Thyroidectomy Thyroid Neoplasms Thyroid Nodule
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Lung Lesion Detection in CT Scan Images Using the Fuzzy Local Information Cluster Means (FLICM) Automatic Segmentation Algorithm and Back Propagation Network Classification.

Asian Pacific journal of cancer prevention : APJCP Dec 29, 2017
Lung cancer is a frequently lethal disease often causing death of human beings at an early age because of uncontrolled cell growth in the lung tissues. The diagnostic methods available are less than effective for detection of cancer. Therefore an aut...
Humans Neural Networks, Computer Algorithms Fuzzy Logic Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Pattern Recognition, Automated Image Processing, Computer-Assisted Lung Neoplasms
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Automated tongue diagnosis on the smartphone and its applications.

Computer methods and programs in biomedicine Dec 24, 2017
Tongue features are important objective basis for clinical diagnosis and treatment in both western medicine and Chinese medicine. The need for continuous monitoring of health conditions inspires us to develop an automatic tongue diagnosis system base...
Smartphone Support Vector Machine Medicine, Chinese Traditional Taiwan Algorithms Temperature Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Liver Diseases Color Equipment Design Lighting Tongue Humans
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Computer-Aided Diagnosis Based on Convolutional Neural Network System for Colorectal Polyp Classification: Preliminary Experience.

Oncology Dec 20, 2017
BACKGROUND AND AIM: Computer-aided diagnosis (CAD) is becoming a next-generation tool for the diagnosis of human disease. CAD for colon polyps has been suggested as a particularly useful tool for trainee colonoscopists, as the use of a CAD system avo...
Humans Neural Networks, Computer Retrospective Studies Colonoscopy Diagnosis, Computer-Assisted Colonic Polyps
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Epileptic Seizures Prediction Using Machine Learning Methods.

Computational and mathematical methods in medicine Dec 19, 2017
Epileptic seizures occur due to disorder in brain functionality which can affect patient's health. Prediction of epileptic seizures before the beginning of the onset is quite useful for preventing the seizure by medication. Machine learning technique...
Support Vector Machine Humans Models, Statistical Seizures Algorithms Electroencephalography Brain Signal Processing, Computer-Assisted Reproducibility of Results Epilepsy Sensitivity and Specificity Diagnosis, Computer-Assisted
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Symtosis: A liver ultrasound tissue characterization and risk stratification in optimized deep learning paradigm.

Computer methods and programs in biomedicine Dec 16, 2017
Background and Objective Fatty Liver Disease (FLD) - a disease caused by deposition of fat in liver cells, is predecessor to terminal diseases such as liver cancer. The machine learning (ML) techniques applied for FLD detection and risk stratificatio...
Support Vector Machine Benchmarking Image Interpretation, Computer-Assisted Ultrasonography ROC Curve Fatty Liver Computational Biology Machine Learning Humans Reproducibility of Results Neural Networks, Computer Risk Factors Diagnosis, Computer-Assisted
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Automated computer-based detection of encounter behaviours in groups of honeybees.

Scientific reports Dec 15, 2017
Honeybees form societies in which thousands of members integrate their behaviours to act as a single functional unit. We have little knowledge on how the collaborative features are regulated by workers' activities because we lack methods that enable ...
Software Automation, Laboratory Animals Diagnosis, Computer-Assisted Machine Learning Bees Behavior, Animal Data Curation Social Behavior
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Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review.

Computer methods and programs in biomedicine Dec 12, 2017
BACKGROUND AND OBJECTIVE: The high incidence of breast cancer in women has increased significantly in the recent years. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerized features extraction and ...
Diagnosis, Computer-Assisted Positron-Emission Tomography Female Image Processing, Computer-Assisted Humans Reproducibility of Results Electronic Data Processing Mammography Machine Learning Sensitivity and Specificity Area Under Curve Databases, Factual Breast Neoplasms Computer Simulation
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Fully Automated Detection and Quantification of Macular Fluid in OCT Using Deep Learning.

Ophthalmology Dec 8, 2017
PURPOSE: Development and validation of a fully automated method to detect and quantify macular fluid in conventional OCT images.
Aged Male Middle Aged Diagnosis, Computer-Assisted Humans Macular Edema Deep Learning Diabetic Retinopathy Female ROC Curve Wet Macular Degeneration Reproducibility of Results Visual Acuity Subretinal Fluid Tomography, Optical Coherence Retinal Vein Occlusion
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Computer-aided diagnosis of contrast-enhanced spectral mammography: A feasibility study.

European journal of radiology Dec 5, 2017
OBJECTIVE: To evaluate whether the use of a computer-aided diagnosis-contrast-enhanced spectral mammography (CAD-CESM) tool can further increase the diagnostic performance of CESM compared with that of experienced radiologists.
Image Enhancement Contrast Media Humans Middle Aged Mammography Algorithms Diagnosis, Computer-Assisted Female Retrospective Studies Image Processing, Computer-Assisted Breast Reproducibility of Results Support Vector Machine Feasibility Studies Sensitivity and Specificity Breast Neoplasms
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