AIMC Topic: Observer Variation
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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
Jun 16, 2023
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)
May 28, 2023
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
Apr 9, 2023
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
Apr 6, 2023
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
Mar 7, 2023
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
Jan 9, 2023
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...
The uncovered biases and errors in clinical determination of bone age by using deep learning models.
European radiology
Dec 20, 2022
OBJECTIVES: To evaluate AI biases and errors in estimating bone age (BA) by comparing AI and radiologists' clinical determinations of BA.
Artificial intelligence and machine learning in cardiotocography: A scoping review.
European journal of obstetrics, gynecology, and reproductive biology
Dec 9, 2022
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 ...
Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI.
European radiology
Nov 12, 2022
OBJECTIVES: Prostate volume (PV) in combination with prostate specific antigen (PSA) yields PSA density which is an increasingly important biomarker. Calculating PV from MRI is a time-consuming, radiologist-dependent task. The aim of this study was t...
Effect of AI-assisted software on inter- and intra-observer variability for the X-ray bone age assessment of preschool children.
BMC pediatrics
Nov 8, 2022
BACKGROUND: With the rapid development of deep learning algorithms and the rapid improvement of computer hardware in the past few years, AI-assisted diagnosis software for bone age has achieved good diagnostic performance. The purpose of this study w...
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