AIMC Topic: Sensitivity and Specificity

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Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.

NeuroImage Oct 6, 2018
The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and long...
Pattern Recognition, Automated Magnetic Resonance Imaging Multiple Sclerosis Spinal Cord Observer Variation Neural Networks, Computer Reproducibility of Results Sensitivity and Specificity Image Processing, Computer-Assisted Humans
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Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients.

JAMA network open Oct 5, 2018
IMPORTANCE: To improve patient safety, health care systems need reliable methods to detect adverse events in large patient populations. Events are often described in clinical notes, rather than structured data, which make them difficult to identify o...
Electronic Health Records Female Aged Aged, 80 and over Humans Machine Learning Support Vector Machine Natural Language Processing Hemorrhage Critical Illness Sensitivity and Specificity Male Middle Aged ROC Curve
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Detection of gastritis by a deep convolutional neural network from double-contrast upper gastrointestinal barium X-ray radiography.

Journal of gastroenterology Oct 3, 2018
BACKGROUND: Deep learning has become a new trend of image recognition tasks in the field of medicine. We developed an automated gastritis detection system using double-contrast upper gastrointestinal barium X-ray radiography.
Humans Neural Networks, Computer Retrospective Studies Deep Learning Radiography Female Gastritis Sensitivity and Specificity False Negative Reactions Male Barium Middle Aged
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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...
Humans Neural Networks, Computer Aged Young Adult Adult Sensitivity and Specificity Male Artificial Intelligence Machine Learning Algorithms Female Urinary Tract Infections False Positive Reactions Cystitis ROC Curve Middle Aged Decision Support Systems, Clinical Diagnosis, Computer-Assisted Support Vector Machine Adolescent Decision Trees Child
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Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

Journal of clinical monitoring and computing Sep 27, 2018
A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majority are difficult to identify even in a post-incident analysis. Changes in some patients' physiolog...
Respiratory Rate Heart Arrest Signal Processing, Computer-Assisted Heart Rate Critical Care Systole Sensitivity and Specificity Infant Child, Preschool Child Intensive Care Units, Pediatric Monitoring, Physiologic Blood Pressure Software Oxygen Critical Illness Infant, Newborn Reproducibility of Results Humans Machine Learning
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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 Automation Sensitivity and Specificity Algorithms Male Inflammation Colonoscopy Middle Aged Retrospective Studies Colitis, Ulcerative Diagnosis, Computer-Assisted Female Colon Intestinal Mucosa Humans Reproducibility of Results Artificial Intelligence Machine Learning
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Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
Effective utilization of multi-center data for autism spectrum disorder (ASD) diagnosis recently has attracted increasing attention, since a large number of subjects from multiple centers are beneficial for investigating the pathological changes of A...
Autism Spectrum Disorder Humans Reproducibility of Results Machine Learning Sensitivity and Specificity Algorithms Databases, Factual
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Multi-task SonoEyeNet: Detection of Fetal Standardized Planes Assisted by Generated Sonographer Attention Maps.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
We present a novel multi-task convolutional neural network called Multi-task SonoEyeNet () that learns to generate clinically relevant visual attention maps using sonographer gaze tracking data on input ultrasound (US) video frames so as to assist st...
Eye Movements Image Processing, Computer-Assisted Attention Fetus Neural Networks, Computer Algorithms Reproducibility of Results Sensitivity and Specificity Humans
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Automatic Lacunae Localization in Placental Ultrasound Images via Layer Aggregation.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
Accurate localization of structural abnormalities is a precursor for image-based prenatal assessment of adverse conditions. For clinical screening and diagnosis of abnormally invasive placenta (AIP), a life-threatening obstetric condition, qualitativ...
Pattern Recognition, Automated Machine Learning Humans Algorithms Reproducibility of Results Pregnancy Sensitivity and Specificity Female Ultrasonography Placenta
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Adversarial Similarity Network for Evaluating Image Alignment in Deep Learning based Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
This paper introduces an unsupervised adversarial similarity network for image registration. Unlike existing deep learning registration frameworks, our approach does not require ground-truth deformations and specific similarity metrics. We connect a ...
Humans Machine Learning Algorithms Brain Reproducibility of Results Sensitivity and Specificity Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging
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