AIMC Topic: Observer Variation
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Super-resolution Deep Learning Reconstruction for 3D Brain MR Imaging: Improvement of Cranial Nerve Depiction and Interobserver Agreement in Evaluations of Neurovascular Conflict.
Academic radiology
Jun 18, 2024
RATIONALE AND OBJECTIVES: To determine if super-resolution deep learning reconstruction (SR-DLR) improves the depiction of cranial nerves and interobserver agreement when assessing neurovascular conflict in 3D fast asymmetric spin echo (3D FASE) brai...
Mammographic density assessment: comparison of radiologists, automated volumetric measurement, and artificial intelligence-based computer-assisted diagnosis.
Acta radiologica (Stockholm, Sweden : 1987)
Jun 2, 2024
BACKGROUND: Artificial intelligence-based computer-assisted diagnosis (AI-CAD) is increasingly used for mammographic exams, and its role in mammographic density assessment should be evaluated.
Artificial intelligence model system for bone age assessment of preschool children.
Pediatric research
May 27, 2024
BACKGROUD: Our study aimed to assess the impact of inter- and intra-observer variations when utilizing an artificial intelligence (AI) system for bone age assessment (BAA) of preschool children.
Artificial Intelligence Helps Pathologists Increase Diagnostic Accuracy and Efficiency in the Detection of Breast Cancer Lymph Node Metastases.
The American journal of surgical pathology
May 27, 2024
The detection of lymph node metastases is essential for breast cancer staging, although it is a tedious and time-consuming task where the sensitivity of pathologists is suboptimal. Artificial intelligence (AI) can help pathologists detect lymph node ...
Automatic assessment of bowel preparation by an artificial intelligence model and its clinical applicability.
Journal of gastroenterology and hepatology
May 20, 2024
BACKGROUND AND AIM: Reliable bowel preparation assessment is important in colonoscopy. However, current scoring systems are limited by laborious and time-consuming tasks and interobserver variability. We aimed to develop an artificial intelligence (A...
Artificial intelligence for gastric cancer in endoscopy: From diagnostic reasoning to market.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
May 18, 2024
Recognition of gastric conditions during endoscopy exams, including gastric cancer, usually requires specialized training and a long learning curve. Besides that, the interobserver variability is frequently high due to the different morphological cha...
Deep Learning Model for Grading and Localization of Lumbar Disc Herniation on Magnetic Resonance Imaging.
Journal of magnetic resonance imaging : JMRI
Apr 27, 2024
BACKGROUND: Methods for grading and localization of lumbar disc herniation (LDH) on MRI are complex, time-consuming, and subjective. Utilizing deep learning (DL) models as assistance would mitigate such complexities.
Super-resolution Deep Learning Reconstruction Cervical Spine 1.5T MRI: Improved Interobserver Agreement in Evaluations of Neuroforaminal Stenosis Compared to Conventional Deep Learning Reconstruction.
Journal of imaging informatics in medicine
Apr 26, 2024
The aim of this study was to investigate whether super-resolution deep learning reconstruction (SR-DLR) is superior to conventional deep learning reconstruction (DLR) with respect to interobserver agreement in the evaluation of neuroforaminal stenosi...
A deep learning-based calculation system for plaque stenosis severity on common carotid artery of ultrasound images.
Vascular
Apr 24, 2024
ObjectivesAssessment of plaque stenosis severity allows better management of carotid source of stroke. Our objective is to create a deep learning (DL) model to segment carotid intima-media thickness and plaque and further automatically calculate plaq...
Reproducibility and prognostic ability of chronicity parameters in kidney biopsy - Comprehensive evaluation comparing microscopy and artificial intelligence in digital pathology.
Human pathology
Apr 18, 2024
INTRODUCTION: Semi-quantitative scoring of various parameters in renal biopsy is accepted as an important tool to assess disease activity and prognostication. There are concerns on the impact of interobserver variability in its prognostic utility, ge...
Humans
Artificial Intelligence
Algorithms
Kidney Transplantation
Prognosis
Biopsy
Female
Fibrosis
Microscopy
Middle Aged
Image Interpretation, Computer-Assisted
Kidney
Reproducibility of Results
Observer Variation
Glomerular Filtration Rate
Polyomavirus Infections
Aged
Kidney Diseases
Adult
Predictive Value of Tests
Male
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