Objective: Endoscopy is an observer-dependent diagnostic method, which, until recently, has lacked precise guidelines for written reports. There is an increasing demand for improvement in endoscopy records, which may necessitate the supplementation of image documentation. The aim of this study was to estimate interobserver as well as intra-observer variability in the assessment of images from gastroscopy.
Material And Methods: We designed an Internet interface presenting endoscopy images, accompanied by a multiple-choice questionnaire for assessing pathology in the images. Ten images from the distal oesophagus and 10 images from the pyloric antrum were chosen. In order to study interobserver variability, physicians with varying endoscopy experience were invited to complete the questionnaire. The physicians were re-invited 5 months later to assess the same images again, this time in order to assess intra-observer variability. Kappa statistics were used for analysis of agreement.
Results: Initially, 13 of 20 invited physicians responded. Interobserver agreement varied between poor (kappa<0.2) and moderate (0.4
Conclusion: The variability in the interpretation of endoscopy images is large. We therefore believe that systematic inclusion of a set of images into endoscopy reports will improve their quality.
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http://dx.doi.org/10.1080/00365520701259240 | DOI Listing |
J Dent
December 2024
OMFS-IMPATH Research Group, Department of Imaging and Pathology, Faculty of Medicine, KU Leuven, Leuven, Belgium; Department of Dental Medicine, Karolinska Institute, Stockholm, Sweden. Electronic address:
Objectives: To validate a novel artificial intelligence (AI)-based tool for automated tooth modelling by fusing cone beam computed tomography (CBCT)-derived roots with corresponding intraoral scanner (IOS)-derived crowns.
Methods: A retrospective dataset of 30 patients, comprising 30 CBCT scans and 55 IOS dental arches, was used to evaluate the fusion model at full arch and single tooth levels. AI-fused models were compared with CBCT tooth segmentation using point-to-point surface distances-reported as median surface distance (MSD), root mean square distance (RMSD), and Hausdorff distance (HD)- alongside visual assessments.
J Crohns Colitis
January 2025
APC Microbiome Ireland, College of Medicine and Health, University College Cork (UCC); Cork, Ireland.
Background And Aims: Achieving histological remission is a desirable emerging treatment target in Ulcerative Colitis (UC), yet its assessment is challenging due to high inter- and intra-observer variability, reliance on experts, and lack of standardisation. Artificial intelligence (AI) holds promise in addressing these issues. This systematic review, meta-analysis, and meta-regression evaluated the AI's performance in assessing histological remission and compared it with that of pathologists.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Fundamental and Clinical Care Nursing, Hospitalet del Llobregat, Universitat de Barcelona, Campus de Bellvitge, Barcelona, Spain.
Objective: To analyse the interrater reliability of the NEUMOBACT checklist and verify whether consistent results are reproducible.
Methods: A validation study with a cross-sectional design, compliant with the GRRAS checklist, among ICU nurses attending a SIMULAZERO course with an Objective Structured Clinical Evaluation simulation format, to verify transfer from theory to clinical practice of knowledge and skills in ventilator-associated pneumonia (VAP) and catheter-related bacteraemia (CRB) prevention. A minimum sample size of 111 pairs of nurse raters was calculated.
Sci Rep
December 2024
Department of Conservative Dentistry, Dental and Life Science Institute, School of Dentistry, Dental Research Institute, Pusan National University, Geumo-ro 20, Mulgeum-eup, Box 50612, Yangsan, Republic of Korea.
The images of the Quantitative Light induced Fluorescent (QLF) device, which provides both natural color images similar to those from intraoral cameras and fluorescent images using 405 nm light in a single shot, were evaluated for the validity and inter examiner reliability in detecting tooth cracks. QLF images of 26 cracked teeth before and after removing crack lines were taken. Two examiners assessed the QLF images before removing the crack line with natural color images, fluorescent images, and combination images showing both images simultaneously, and recorded the crack's location after observing images.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Oral Medicine and Radiology, Teerthanker Mahaveer Dental College and Research Centre, Moradabad, Uttar Pradesh, India.
A novel classification system, termed the Sivan classification, was developed to enhance the diagnosis of jaw lesions by utilizing visual volumetric analysis of three-dimensional Cone Beam Computed Tomography (CBCT) images. This classification groups lesions into ten categories, primarily divided into hypovolumetric, hypervolumetric, and normovolumetric groups. To validate this system, 10 raters-comprising 5 general dentists and 5 oral radiology specialists-assessed the CBCT images and diagnosed the lesions using the Sivan classification.
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