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Observer Variation

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Analyzing inter-reader variability affecting deep ensemble learning for COVID-19 detection in chest radiographs.

PloS one Nov 12, 2020
Data-driven deep learning (DL) methods using convolutional neural networks (CNNs) demonstrate promising performance in natural image computer vision tasks. However, their use in medical computer vision tasks faces several limitations, viz., (i) adapt...
Observer Variation Algorithms Humans Radiography, Thoracic SARS-CoV-2 Neural Networks, Computer Betacoronavirus Deep Learning Pandemics Pneumonia, Viral Image Processing, Computer-Assisted COVID-19 Coronavirus Infections
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A Prospective Validation and Observer Performance Study of a Deep Learning Algorithm for Pathologic Diagnosis of Gastric Tumors in Endoscopic Biopsies.

Clinical cancer research : an official journal of the American Association for Cancer Research Nov 10, 2020
PURPOSE: Gastric cancer remains the leading cause of cancer-related deaths in Northeast Asia. Population-based endoscopic screenings in the region have yielded successful results in early detection of gastric tumors. Endoscopic screening rates are co...
Aged Aged, 80 and over Adult Stomach Neoplasms Sensitivity and Specificity Humans Prospective Studies Retrospective Studies Female Pathologists Image Interpretation, Computer-Assisted Observer Variation Gastroscopy Gastric Mucosa Male Middle Aged Deep Learning Biopsy Feasibility Studies
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Automatic Segmentation Using Deep Learning to Enable Online Dose Optimization During Adaptive Radiation Therapy of Cervical Cancer.

International journal of radiation oncology, biology, physics Nov 9, 2020
PURPOSE: This study investigated deep learning models for automatic segmentation to support the development of daily online dose optimization strategies, eliminating the need for internal target volume expansions and thereby reducing toxicity events ...
Humans Retrospective Studies Tomography, X-Ray Computed Female Uterine Cervical Neoplasms Deep Learning Radiotherapy Planning, Computer-Assisted Observer Variation Radiotherapy Dosage
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Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate Cancers.

JAMA network open Nov 2, 2020
IMPORTANCE: Personalized radiotherapy planning depends on high-quality delineation of target tumors and surrounding organs at risk (OARs). This process puts additional time burdens on oncologists and introduces variability among both experts and inst...
Neural Networks, Computer Tomography, X-Ray Computed Reproducibility of Results Aged Male Humans Organs at Risk Quality Improvement Observer Variation Radiotherapy, Intensity-Modulated Middle Aged Radiotherapy, Image-Guided Deep Learning Head and Neck Neoplasms Prostatic Neoplasms
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Traditional and New Methods of Bone Age Assessment-An Overview.

Journal of clinical research in pediatric endocrinology Oct 26, 2020
Bone age is one of biological indicators of maturity used in clinical practice and it is a very important parameter of a child’s assessment, especially in paediatric endocrinology. The most widely used method of bone age assessment is by performing a...
Young Adult Male Infant Diagnosis, Computer-Assisted Deep Learning Adolescent Child, Preschool Child Age Factors Humans Neural Networks, Computer Female Infant, Newborn Reproducibility of Results Child Development Predictive Value of Tests Wrist Joint Radiographic Image Interpretation, Computer-Assisted Age Determination by Skeleton Observer Variation Adolescent Development Automation Hand Bones
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Central Reading of Ulcerative Colitis Clinical Trial Videos Using Neural Networks.

Gastroenterology Oct 21, 2020
BACKGROUND AND AIMS: Endoscopic disease activity scoring in ulcerative colitis (UC) is useful in clinical practice but done infrequently. It is required in clinical trials, where it is expensive and slow because human central readers are needed. A ma...
Video Recording Image Interpretation, Computer-Assisted Observer Variation Antibodies, Monoclonal, Humanized Humans Colitis, Ulcerative Severity of Illness Index Prospective Studies Intestinal Mucosa Deep Learning Female Predictive Value of Tests Adolescent Aged Feasibility Studies Treatment Outcome Adult Young Adult Male Middle Aged Colon Colonoscopy
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Deep learning for elective neck delineation: More consistent and time efficient.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Oct 14, 2020
BACKGROUND/PURPOSE: Delineation of the lymph node levels of the neck for irradiation of the elective clinical target volume in head and neck cancer (HNC) patients is time consuming and prone to interobserver variability (IOV), although international ...
Humans Neural Networks, Computer Deep Learning Head and Neck Neoplasms Neoplasm Staging Observer Variation
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Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis.

Gut Oct 7, 2020
OBJECTIVE: The diagnosis of autoimmune pancreatitis (AIP) is challenging. Sonographic and cross-sectional imaging findings of AIP closely mimic pancreatic ductal adenocarcinoma (PDAC) and techniques for tissue sampling of AIP are suboptimal. These li...
Diagnosis, Differential Pancreatic Neoplasms Area Under Curve Carcinoma, Pancreatic Ductal Endosonography Humans Neural Networks, Computer Machine Learning ROC Curve Image Interpretation, Computer-Assisted Observer Variation Pancreas Autoimmune Pancreatitis
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Brain tumor segmentation using 3D Mask R-CNN for dynamic susceptibility contrast enhanced perfusion imaging.

Physics in medicine and biology Sep 18, 2020
The segmentation of neoplasms is an important part of radiotherapy treatment planning, monitoring disease progression, and predicting patient outcome. In the brain, functional magnetic resonance imaging (MRI) like dynamic susceptibility contrast enha...
Imaging, Three-Dimensional Humans Contrast Media Neural Networks, Computer Observer Variation Retrospective Studies Perfusion Imaging Brain Neoplasms
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Convolutional neural networks versus radiologists in characterization of small hypoattenuating hepatic nodules on CT: a critical diagnostic challenge in staging of colorectal carcinoma.

Scientific reports Sep 17, 2020
Our objective was to compare the diagnostic performance and diagnostic confidence of convolutional neural networks (CNN) to radiologists in characterizing small hypoattenuating hepatic nodules (SHHN) in colorectal carcinoma (CRC) on CT scans. Retrosp...
Colorectal Neoplasms Male Middle Aged Diagnosis, Computer-Assisted Liver Neoplasms Aged Aged, 80 and over Young Adult Humans Adult Neural Networks, Computer Expert Testimony Retrospective Studies Liver Tomography, X-Ray Computed Neoplasm Staging Female Radiologists Radiographic Image Interpretation, Computer-Assisted Observer Variation
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