AIMC Topic: Sensitivity and Specificity

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Small lung nodules detection based on local variance analysis and probabilistic neural network.

Computer methods and programs in biomedicine Apr 28, 2018
BACKGROUND AND OBJECTIVE: In medical examinations doctors use various techniques in order to provide to the patients an accurate analysis of their actual state of health. One of the commonly used methodologies is the x-ray screening. This examination...
Reproducibility of Results Sensitivity and Specificity Lung Image Processing, Computer-Assisted Lung Neoplasms Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Carcinoma Probability Pattern Recognition, Automated Humans Neural Networks, Computer Algorithms Databases, Factual False Positive Reactions X-Rays Radiographic Image Enhancement Medical Errors
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Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

Archives of toxicology Apr 28, 2018
Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide ...
Bronchi Xenobiotics Humans Cell Survival Artificial Intelligence Predictive Value of Tests Sensitivity and Specificity A549 Cells Lung High-Throughput Screening Assays Cell Line Toxicity Tests
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An improved deep learning approach for detection of thyroid papillary cancer in ultrasound images.

Scientific reports Apr 26, 2018
Unlike daily routine images, ultrasound images are usually monochrome and low-resolution. In ultrasound images, the cancer regions are usually blurred, vague margin and irregular in shape. Moreover, the features of cancer region are very similar to n...
Child Ultrasonography ROC Curve Image Processing, Computer-Assisted Thyroid Cancer, Papillary Sensitivity and Specificity Male Middle Aged Deep Learning Adolescent Humans Software Algorithms Female Aged Aged, 80 and over Young Adult Adult
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Detection of white matter lesion regions in MRI using SLIC0 and convolutional neural network.

Computer methods and programs in biomedicine Apr 19, 2018
BACKGROUND AND OBJECTIVE: White matter lesions are non-static brain lesions that have a prevalence rate up to 98% in the elderly population. Because they may be associated with several brain diseases, it is important that they are detected as soon as...
Sensitivity and Specificity Prevalence Diagnosis, Computer-Assisted Deep Learning Magnetic Resonance Imaging Humans Neural Networks, Computer Image Processing, Computer-Assisted Pattern Recognition, Automated Algorithms False Positive Reactions Databases, Factual White Matter Brain Reproducibility of Results
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Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.

Journal of magnetic resonance imaging : JMRI Apr 16, 2018
BACKGROUND: Deep learning is the most promising methodology for automatic computer-aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp-MRI).
Reproducibility of Results Sensitivity and Specificity Male Diagnosis, Computer-Assisted Deep Learning Humans Neural Networks, Computer Software Databases, Factual Retrospective Studies Diffusion Magnetic Resonance Imaging ROC Curve Predictive Value of Tests Area Under Curve Prostatic Neoplasms Pattern Recognition, Automated
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Classifying Acute Ischemic Stroke Onset Time using Deep Imaging Features.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
Models have been developed to predict stroke outcomes (e.g., mortality) in attempt to provide better guidance for stroke treatment. However, there is little work in developing classification models for the problem of unknown time-since-stroke (TSS), ...
ROC Curve Support Vector Machine Magnetic Resonance Imaging Aged Humans Stroke Sensitivity and Specificity Brain Ischemia Machine Learning Regression Analysis Male Prognosis Area Under Curve Middle Aged Female Deep Learning
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Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling.

Radiology Apr 10, 2018
Purpose To compare two technical approaches for determination of coronary computed tomography (CT) angiography-derived fractional flow reserve (FFR)-FFR derived from coronary CT angiography based on computational fluid dynamics (hereafter, FFR) and F...
Machine Learning Algorithms Retrospective Studies Female Reproducibility of Results Humans Coronary Angiography Hydrodynamics Computed Tomography Angiography Coronary Stenosis Sensitivity and Specificity Fractional Flow Reserve, Myocardial Male Middle Aged Hemodynamics Predictive Value of Tests
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Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning.

Epilepsia Apr 10, 2018
OBJECTIVE: Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In ...
Area Under Curve Epilepsy Neuroimaging Malformations of Cortical Development, Group I Young Adult Adult Sensitivity and Specificity Male Middle Aged Humans Adolescent Machine Learning Child, Preschool Brain Child Female ROC Curve Magnetic Resonance Imaging
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Abnormal brain structure as a potential biomarker for venous erectile dysfunction: evidence from multimodal MRI and machine learning.

European radiology Mar 29, 2018
OBJECTIVES: To investigate the cerebral structural changes related to venous erectile dysfunction (VED) and the relationship of these changes to clinical symptoms and disorder duration and distinguish patients with VED from healthy controls using a m...
Diffusion Tensor Imaging Magnetic Resonance Imaging Brain Mapping Multimodal Imaging Brain Diseases Erectile Dysfunction Brain Humans Reproducibility of Results Machine Learning Adult Biomarkers Sensitivity and Specificity Male
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Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

Academic radiology Mar 28, 2018
RATIONALE AND OBJECTIVES: To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four hea...
Middle Aged Humans Aged Lumbar Vertebrae Aged, 80 and over Machine Learning Cohort Studies Low Back Pain Female Magnetic Resonance Imaging Adult Natural Language Processing Sensitivity and Specificity Radiography Male
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