AIMC Topic: Sensitivity and Specificity

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Diagnostic assessment of a deep learning system for detecting atrial fibrillation in pulse waveforms.

Heart (British Cardiac Society) May 31, 2018
OBJECTIVE: To evaluate the diagnostic performance of a deep learning system for automated detection of atrial fibrillation (AF) in photoplethysmographic (PPG) pulse waveforms.
Female Aged Sensitivity and Specificity Male Middle Aged Deep Learning Smartphone Photoplethysmography Electrocardiography Comparative Effectiveness Research Humans Telemedicine Atrial Fibrillation Monitoring, Ambulatory Ventricular Premature Complexes Dimensional Measurement Accuracy
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Using machine-learning approaches to predict non-participation in a nationwide general health check-up scheme.

Computer methods and programs in biomedicine May 29, 2018
BACKGROUND: In the time since the launch of a nationwide general health check-up and instruction program in Japan in 2008, interest in the formulation of an effective and efficient strategy to improve the participation rate has been growing. The aim ...
Normal Distribution Male Middle Aged ROC Curve Support Vector Machine Humans Retrospective Studies Logistic Models Health Status Machine Learning Female Area Under Curve Algorithms Aged Patient Compliance Databases, Factual Adult Japan Sensitivity and Specificity
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Prediction of radiographic abnormalities by the use of bag-of-features and convolutional neural networks.

Veterinary journal (London, England : 1997) May 29, 2018
This study evaluated the feasibility of bag-of-features (BOF) and convolutional neural networks (CNN) for computer-aided detection in distinguishing normal from abnormal radiographic findings. Computed thoracic radiographs of dogs were collected. For...
Animals Diagnosis, Computer-Assisted Lung Diseases Dogs Dog Diseases Neural Networks, Computer Heart Diseases Reproducibility of Results Sensitivity and Specificity Radiography, Thoracic
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Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.

Journal of clinical monitoring and computing May 24, 2018
Traumatically brain injured (TBI) patients are at risk from secondary insults. Arterial hypotension, critically low blood pressure, is one of the most dangerous secondary insults and is related to poor outcome in patients. The overall aim of this stu...
Signal Processing, Computer-Assisted Hypotension Brain Injuries, Traumatic Databases, Factual Critical Care Brain Injuries Prospective Studies False Positive Reactions Area Under Curve Intensive Care Units Middle Aged Sample Size Female Humans Diagnosis, Computer-Assisted Bayes Theorem Aged Aged, 80 and over Neural Networks, Computer Pilot Projects Machine Learning Young Adult Adolescent Software Adult Sensitivity and Specificity Male
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Novel Breast Imaging and Machine Learning: Predicting Breast Lesion Malignancy at Cone-Beam CT Using Machine Learning Techniques.

AJR. American journal of roentgenology May 24, 2018
OBJECTIVE: The purpose of this study is to evaluate the diagnostic performance of machine learning techniques for malignancy prediction at breast cone-beam CT (CBCT) and to compare them to human readers.
Prospective Studies Female Sensitivity and Specificity Breast Neoplasms Middle Aged Humans Machine Learning Cone-Beam Computed Tomography Contrast Media Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Iohexol
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Analysis of hepatitis B virus infection in blood sera using Raman spectroscopy and machine learning.

Photodiagnosis and photodynamic therapy May 19, 2018
This study presents the analysis of hepatitis B virus (HBV) infection in human blood serum using Raman spectroscopy combined with pattern recognition technique. In total, 119 confirmed samples of HBV infected sera, collected from Pakistan Atomic Ener...
Humans Algorithms Sensitivity and Specificity Diagnostic Errors Hepatitis B Serum Image Processing, Computer-Assisted Spectrum Analysis, Raman Support Vector Machine Pattern Recognition, Automated
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Machine Learning for Outcome Prediction in Electroencephalograph (EEG)-Monitored Children in the Intensive Care Unit.

Journal of child neurology May 13, 2018
The aim of this study was to evaluate the performance of models predicting in-hospital mortality in critically ill children undergoing continuous electroencephalography (cEEG) in the intensive care unit (ICU). We evaluated the performance of machine ...
Critical Care Infant, Newborn Area Under Curve Neurophysiological Monitoring Young Adult Humans Electroencephalography Sensitivity and Specificity Diagnosis, Computer-Assisted Machine Learning Epilepsy Male Prognosis Adolescent Seizures Infant Female Child, Preschool Child Hospital Mortality
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A Deep Learning Approach for Targeted Contrast-Enhanced Ultrasound Based Prostate Cancer Detection.

IEEE/ACM transactions on computational biology and bioinformatics May 11, 2018
The important role of angiogenesis in cancer development has driven many researchers to investigate the prospects of noninvasive cancer diagnosis based on the technology of contrast-enhanced ultrasound (CEUS) imaging. This paper presents a deep learn...
Area Under Curve Prostatic Neoplasms Video Recording Reproducibility of Results Neoplasm Transplantation Humans Sensitivity and Specificity Neural Networks, Computer Image Processing, Computer-Assisted Male Algorithms Computational Biology Deep Learning Contrast Media Ultrasonography Models, Statistical
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Accuracy of ultra-wide-field fundus ophthalmoscopy-assisted deep learning, a machine-learning technology, for detecting age-related macular degeneration.

International ophthalmology May 9, 2018
PURPOSE: To predict exudative age-related macular degeneration (AMD), we combined a deep convolutional neural network (DCNN), a machine-learning algorithm, with Optos, an ultra-wide-field fundus imaging system.
Humans Neural Networks, Computer Algorithms Female Aged Aged, 80 and over Sensitivity and Specificity Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Ophthalmoscopy Wet Macular Degeneration
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Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram.

Neural networks : the official journal of the International Neural Network Society May 7, 2018
Seizure prediction has attracted growing attention as one of the most challenging predictive data analysis efforts to improve the life of patients with drug-resistant epilepsy and tonic seizures. Many outstanding studies have reported great results i...
Seizures Fourier Analysis Humans Neural Networks, Computer Sensitivity and Specificity Child Electroencephalography
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