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Observer Variation

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Accelerated Measurement of Carotid Plaque Volume Using Artificial Intelligence Enhanced 3D Ultrasound.

Annals of vascular surgery
BACKGROUND: Carotid plaque volume (CPV) can be measured by 3D ultrasound and may be a better predictor of stroke than stenosis, but analysis time limits clinical utility. This study tested the accuracy, reproducibility, and time saved of using an art...

An investigation into the risk of population bias in deep learning autocontouring.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: To date, data used in the development of Deep Learning-based automatic contouring (DLC) algorithms have been largely sourced from single geographic populations. This study aimed to evaluate the risk of population-based bias by...

Screening outcome for interpretation by the first and second reader in a population-based mammographic screening program with independent double reading.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Double reading of screening mammograms is associated with a higher rate of screen-detected cancer than single reading, but different strategies exist regarding reader pairing and blinding. Knowledge about these aspects is important when c...

Convolutional neural network-based model observer for signal known statistically task in breast tomosynthesis images.

Medical physics
BACKGROUND: Since human observer studies are resource-intensive, mathematical model observers are frequently used to assess task-based image quality. The most common implementation of these model observers assume that the signal information is exactl...

A comparative study of the inter-observer variability on Gleason grading against Deep Learning-based approaches for prostate cancer.

Computers in biology and medicine
BACKGROUND: Among all the cancers known today, prostate cancer is one of the most commonly diagnosed in men. With modern advances in medicine, its mortality has been considerably reduced. However, it is still a leading type of cancer in terms of deat...

Clinicians' perception of oral potentially malignant disorders: a pitfall for image annotation in supervised learning.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: The present study aims to quantify clinicians' perceptions of oral potentially malignant disorders (OPMDs) when evaluating, classifying, and manually annotating clinical images, as well as to understand the source of inter-observer variabi...

Anastomotic perfusion assessment with indocyanine green in robot-assisted low-anterior resection, a multicenter study of interobserver variation.

Surgical endoscopy
BACKGROUND: Securing sufficient blood perfusion to the anastomotic area after low-anterior resection is a crucial factor in preventing anastomotic leakage (AL). Intra-operative indocyanine green fluorescent imaging (ICG-FI) has been suggested as a to...

Artificial intelligence and machine learning in cardiotocography: A scoping review.

European journal of obstetrics, gynecology, and reproductive biology
INTRODUCTION: Artificial intelligence (AI) is gaining more interest in the field of medicine due to its capacity to learn patterns directly from data. This becomes interesting for the field of cardiotocography (CTG) interpretation, since it promises ...

Automatic GRBAS Scoring of Pathological Voices using Deep Learning and a Small Set of Labeled Voice Data.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Auditory-perceptual evaluation frameworks, such as the grade-roughness-breathiness-asthenia-strain (GRBAS) scale, are the gold standard for the quantitative evaluation of pathological voice quality. However, the evaluation is subjective; ...