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Observer Variation

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Detection of early infarction signs with machine learning-based diagnosis by means of the Alberta Stroke Program Early CT score (ASPECTS) in the clinical routine.

Neuroradiology Jul 31, 2018
PURPOSE: New software solutions emerged to support radiologists in image interpretation in acute ischemic stroke. This study aimed to validate the performance of computer-aided assessment of the Alberta Stroke Program Early CT score (ASPECTS) for det...
Observer Variation Alberta Aged, 80 and over Adult Sensitivity and Specificity Male Middle Aged Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Stroke Infarction, Middle Cerebral Artery Brain Ischemia Machine Learning Software Tomography, X-Ray Computed Female Aged Humans
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A machine-learning framework for automatic reference-free quality assessment in MRI.

Magnetic resonance imaging Jul 21, 2018
Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large amount of data is created per examination which needs to be checked for sufficient quality in order to derive a meaningful diagnosis. This is a manual process and th...
Prospective Studies Retrospective Studies Female Aged Adult Support Vector Machine Male Humans Magnetic Resonance Imaging Middle Aged Neural Networks, Computer Signal Processing, Computer-Assisted Deep Learning Databases, Factual Observer Variation ROC Curve Fourier Analysis Image Processing, Computer-Assisted
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Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.

Gastroenterology Jun 18, 2018
BACKGROUND & AIMS: The benefit of colonoscopy for colorectal cancer prevention depends on the adenoma detection rate (ADR). The ADR should reflect the adenoma prevalence rate, which is estimated to be higher than 50% in the screening-age population. ...
Humans Neural Networks, Computer Machine Learning Prognosis Early Detection of Cancer Predictive Value of Tests Area Under Curve Feasibility Studies Colonic Polyps Reproducibility of Results Colorectal Neoplasms Colonoscopy Diagnosis, Computer-Assisted ROC Curve Video Recording Image Interpretation, Computer-Assisted Observer Variation Adenomatous Polyps
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Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images.

PloS one May 9, 2018
In pathology, Immunohistochemical staining (IHC) of tissue sections is regularly used to diagnose and grade malignant tumors. Typically, IHC stain interpretation is rendered by a trained pathologist using a manual method, which consists of counting e...
Immunohistochemistry Phantoms, Imaging Ki-67 Antigen Neural Networks, Computer Humans Female Image Processing, Computer-Assisted Antigens, Neoplasm Observer Variation
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Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis.

Computers in biology and medicine Apr 27, 2018
A large amount of digital image material is routinely captured during esophagogastroduodenoscopies but, for the most part, is not used for confirming the diagnosis process of celiac disease which is primarily based on histological examination of biop...
Celiac Disease Image Interpretation, Computer-Assisted Observer Variation Automation Pattern Recognition, Automated Gastroscopy Neural Networks, Computer Machine Learning Algorithms Endoscopy Diagnosis, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Duodenum Decision Making Biopsy Humans
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Using support vector machine analysis to assess PartinMR: A new prediction model for organ-confined prostate cancer.

Journal of magnetic resonance imaging : JMRI Feb 13, 2018
BACKGROUND: Partin tables represent the most widely used predictive tool for prostate cancer stage at prostatectomy but with potential limitations.
Prostatic Neoplasms Biopsy Observer Variation Humans Proportional Hazards Models Software Algorithms Image Processing, Computer-Assisted Retrospective Studies Support Vector Machine Reproducibility of Results Magnetic Resonance Imaging Aged Area Under Curve Male Middle Aged
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Deep Learning Algorithm for Auto-Delineation of High-Risk Oropharyngeal Clinical Target Volumes With Built-In Dice Similarity Coefficient Parameter Optimization Function.

International journal of radiation oncology, biology, physics Feb 7, 2018
PURPOSE: Automating and standardizing the contouring of clinical target volumes (CTVs) can reduce interphysician variability, which is one of the largest sources of uncertainty in head and neck radiation therapy. In addition to using uniform margin e...
Observer Variation Oropharyngeal Neoplasms Humans Algorithms Deep Learning Head and Neck Neoplasms Tumor Burden
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Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study.

The British journal of radiology Jan 10, 2018
OBJECTIVE: To train a generic deep learning software (DLS) to classify breast cancer on ultrasound images and to compare its performance to human readers with variable breast imaging experience.
Software Algorithms Retrospective Studies Female Aged Aged, 80 and over Adult Breast Neoplasms Middle Aged Clinical Competence Humans Machine Learning Adolescent Switzerland Ultrasonography, Mammary Image Interpretation, Computer-Assisted Observer Variation
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Quantitative Assessment of the Physiological Parameters Influencing QT Interval Response to Medication: Application of Computational Intelligence Tools.

Computational and mathematical methods in medicine Jan 4, 2018
Human heart electrophysiology is complex biological phenomenon, which is indirectly assessed by the measured ECG signal. ECG trace is further analyzed to derive interpretable surrogates including QT interval, QRS complex, PR interval, and T wave morp...
Risk Electrophysiology Terfenadine Myocytes, Cardiac Observer Variation Clinical Trials as Topic Cell Membrane Software Algorithms Reproducibility of Results Electrocardiography Action Potentials Humans Artificial Intelligence Calcium Arrhythmias, Cardiac Ions Sodium Programming Languages Models, Statistical Regression Analysis Heart Potassium Anti-Arrhythmia Agents
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Fully automated, deep learning segmentation of oxygen-induced retinopathy images.

JCI insight Dec 21, 2017
Oxygen-induced retinopathy (OIR) is a widely used model to study ischemia-driven neovascularization (NV) in the retina and to serve in proof-of-concept studies in evaluating antiangiogenic drugs for ocular, as well as nonocular, diseases. The primary...
Oxygen Observer Variation Mice, Transgenic Retinal Neovascularization Deep Learning Image Processing, Computer-Assisted Microscopy, Confocal Disease Models, Animal Mice, Inbred C57BL Algorithms Female Animals Male
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