AIMC Topic: Sensitivity and Specificity

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Artificial Intelligence-Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI.

Investigative radiology Jun 1, 2019
OBJECTIVES: We investigated artificial intelligence (AI)-based classification of benign and malignant breast lesions imaged with a multiparametric breast magnetic resonance imaging (MRI) protocol with ultrafast dynamic contrast-enhanced MRI, T2-weigh...
Humans Artificial Intelligence Retrospective Studies Female ROC Curve Contrast Media Breast Image Enhancement Diffusion Magnetic Resonance Imaging Adult Sensitivity and Specificity Breast Neoplasms Middle Aged Multiparametric Magnetic Resonance Imaging
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Deep transfer learning-based prostate cancer classification using 3 Tesla multi-parametric MRI.

Abdominal radiology (New York) Jun 1, 2019
PURPOSE: The purpose of the study was to propose a deep transfer learning (DTL)-based model to distinguish indolent from clinically significant prostate cancer (PCa) lesions and to compare the DTL-based model with a deep learning (DL) model without t...
Male Aged Biopsy Humans Diagnosis, Differential Middle Aged Image Interpretation, Computer-Assisted Aged, 80 and over Software Deep Learning Prostatic Neoplasms Adult Retrospective Studies Magnetic Resonance Imaging Sensitivity and Specificity
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Robot Diagnosis Test for Egocentric and Allocentric Hemineglect.

Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists Jun 1, 2019
OBJECTIVE: Patients with hemineglect fail to respond to egocentric stimuli or allocentric parts of stimuli contralateral to the brain lesion. The clinical diagnosis of hemineglect mainly involves evaluation of the egocentric form, while less sensitiv...
Adult Sensitivity and Specificity Male Middle Aged Case-Control Studies Female Reproducibility of Results Aged Aged, 80 and over Attention Functional Laterality Neuropsychological Tests Space Perception Perceptual Disorders Humans Diagnosis, Computer-Assisted Robotics Stroke Reference Values
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Burn wound classification model using spatial frequency-domain imaging and machine learning.

Journal of biomedical optics May 1, 2019
Accurate assessment of burn severity is critical for wound care and the course of treatment. Delays in classification translate to delays in burn management, increasing the risk of scarring and infection. To this end, numerous imaging techniques have...
Software Algorithms Reproducibility of Results Sensitivity and Specificity Severity of Illness Index Support Vector Machine Wound Healing Animals Swine Machine Learning Color Calibration Skin Optical Imaging Burns Optics and Photonics Light
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Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography.

Korean journal of radiology May 1, 2019
OBJECTIVE: To investigate whether a computer-aided diagnosis (CAD) system based on a deep learning framework (deep learning-based CAD) improves the diagnostic performance of radiologists in differentiating between malignant and benign masses on breas...
Image Processing, Computer-Assisted Retrospective Studies Area Under Curve Female Breast Adult Sensitivity and Specificity Humans Deep Learning Breast Neoplasms Ultrasonography Middle Aged ROC Curve
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Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram.

JAMA cardiology May 1, 2019
IMPORTANCE: For patients with chronic kidney disease (CKD), hyperkalemia is common, associated with fatal arrhythmias, and often asymptomatic, while guideline-directed monitoring of serum potassium is underused. A deep-learning model that enables non...
Renal Insufficiency, Chronic Mass Screening Arrhythmias, Cardiac Hyperkalemia Female Aged Aged, 80 and over Sensitivity and Specificity Prevalence Deep Learning Electrocardiography Male Middle Aged Neural Networks, Computer Artificial Intelligence Algorithms Retrospective Studies Humans
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[Deep residual convolutional neural network for recognition of electrocardiogram signal arrhythmias].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Apr 25, 2019
Electrocardiogram (ECG) signals are easily disturbed by internal and external noise, and its morphological characteristics show significant variations for different patients. Even for the same patient, its characteristics are variable under different...
Heart Rate Algorithms Sensitivity and Specificity Electrocardiography Humans Arrhythmias, Cardiac Neural Networks, Computer
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Computational neural network in melanocytic lesions diagnosis: artificial intelligence to improve diagnosis in dermatology?

European journal of dermatology : EJD Apr 1, 2019
Diagnosis in dermatology is largely based on contextual factors going far beyond the visual and dermoscopic inspection of a lesion. Diagnostic tools such as the different types of dermoscopy, confocal microscopy and optical coherence tomography (OCT)...
Deep Learning Melanocytes Humans Image Processing, Computer-Assisted Melanoma Microscopy, Confocal Skin Skin Neoplasms Tomography, Optical Coherence Dermoscopy Neural Networks, Computer Dermatology Sensitivity and Specificity Artificial Intelligence Algorithms
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Predicting Breast Cancer Molecular Subtype with MRI Dataset Utilizing Convolutional Neural Network Algorithm.

Journal of digital imaging Apr 1, 2019
To develop a convolutional neural network (CNN) algorithm that can predict the molecular subtype of a breast cancer based on MRI features. An IRB-approved study was performed in 216 patients with available pre-treatment MRIs and immunohistochemical s...
Humans Neural Networks, Computer Algorithms Magnetic Resonance Imaging Retrospective Studies Image Interpretation, Computer-Assisted Predictive Value of Tests Female Sensitivity and Specificity Breast Neoplasms
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Automatic Labeling of Special Diagnostic Mammography Views from Images and DICOM Headers.

Journal of digital imaging Apr 1, 2019
Applying state-of-the-art machine learning techniques to medical images requires a thorough selection and normalization of input data. One of such steps in digital mammography screening for breast cancer is the labeling and removal of special diagnos...
Datasets as Topic Automation Radiology Information Systems Female Sensitivity and Specificity Breast Neoplasms Humans Mammography Machine Learning
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