Cargando…

Using Machine Learning Methods Incorporating Individual Reader Annotations to Classify Paediatric Chest Radiographs in Epidemiological Studies

Introduction: Epidemiological studies that involve interpretation of chest radiographs (CXRs) suffer from inter-reader and intra-reader variability. Inter-reader and intra-reader variability hinder comparison of results from different studies or centres, which negatively affects efforts to track the...

Descripción completa

Detalles Bibliográficos
Autores principales:	Mwaniki, Paul, Kamanu, Timothy, Akech, Samuel, Eijkemans, M. J. C
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	F1000 Research Limited 2022
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9463539/ https://www.ncbi.nlm.nih.gov/pubmed/36111213 http://dx.doi.org/10.12688/wellcomeopenres.17164.2

Ejemplares similares

Using self-supervised feature learning to improve the use of pulse oximeter signals to predict paediatric hospitalization
por: Mwaniki, Paul, et al.
Publicado: (2023)

Association of Artificial Intelligence–Aided Chest Radiograph Interpretation With Reader Performance and Efficiency
por: Ahn, Jong Seok, et al.
Publicado: (2022)

Accuracy of the Interpretation of Chest Radiographs for the Diagnosis of Paediatric Pneumonia
por: Elemraid, Mohamed A., et al.
Publicado: (2014)

Incorporation of biomarkers into a prediction model for paediatric radiographic pneumonia
por: Ramgopal, Sriram, et al.
Publicado: (2023)

Unilateral opaque chest radiograph in paediatrics: A case series
por: Raja Mamat, Tengku A., et al.
Publicado: (2021)

Molecular Evolution. An Annotated Reader
por: Mockovak, Michael
Publicado: (1985)

Pilot Evaluation of an Online Resource for Learning Paediatric Chest Radiograph Interpretation
por: Rajendran, Karthik, et al.
Publicado: (2021)

Analyzing inter-reader variability affecting deep ensemble learning for COVID-19 detection in chest radiographs
por: Rajaraman, Sivaramakrishnan, et al.
Publicado: (2020)

VariantClassifier: A hierarchical variant classifier for annotated genomes
por: Li, Kelvin, et al.
Publicado: (2010)

Human–machine partnership with artificial intelligence for chest radiograph diagnosis
por: Patel, Bhavik N., et al.
Publicado: (2019)

Added Value of Bone Suppression Image in the Detection of Subtle Lung Lesions on Chest Radiographs with Regard to Reader's Expertise
por: Hong, Gil-Sun, et al.
Publicado: (2019)

Chest radiographs and machine learning – Past, present and future
por: Jones, Catherine M, et al.
Publicado: (2021)

Efficacy of Artificial Intelligence in the Categorisation of Paediatric Pneumonia on Chest Radiographs: A Systematic Review
por: Field, Erica Louise, et al.
Publicado: (2023)

Imaging the Chest: The Chest Radiograph
por: Broder, Joshua
Publicado: (2011)

The 2021 SIIM-FISABIO-RSNA Machine Learning COVID-19 Challenge: Annotation and Standard Exam Classification of COVID-19 Chest Radiographs
por: Lakhani, Paras, et al.
Publicado: (2022)

The Chest Radiograph
por: Kelly, Barry
Publicado: (2012)

Localization supervision of chest x-ray classifiers using label-specific eye-tracking annotation
por: Bigolin Lanfredi, Ricardo, et al.
Publicado: (2023)

Workforce issues in breast imaging: radiographers as screen readers
por: Bennett, RL, et al.
Publicado: (2006)

Author Correction: Human–machine partnership with artificial intelligence for chest radiograph diagnosis
por: Patel, Bhavik N., et al.
Publicado: (2019)

Chest radiograph classification and severity of suspected COVID-19 by different radiologist groups and attending clinicians: multi-reader, multi-case study
por: Nair, Arjun, et al.
Publicado: (2022)

An evaluation of the current role of radiographer film readers in breast screening
por: Williams, B, et al.
Publicado: (2002)

Utility of routine chest radiographs after chest drain removal in paediatric cardiac surgical patients—a retrospective analysis of 1076 patients
por: Shetty, Gautham, et al.
Publicado: (2023)

Deep learning-based cardiothoracic ratio measurement on chest radiograph: accuracy improvement without self-annotation
por: Yoshida, Kotaro, et al.
Publicado: (2023)

Multi-Reader–Multi-Split Annotation of Emphysema in Computed Tomography
por: Lidén, Mats, et al.
Publicado: (2020)

Artificial intelligence-supported lung cancer detection by multi-institutional readers with multi-vendor chest radiographs: a retrospective clinical validation study
por: Ueda, Daiju, et al.
Publicado: (2021)

The Use of Chest Radiographs and Machine Learning Model for the Rapid Detection of Pneumonitis in Pediatric
por: Alshamrani, Khalaf, et al.
Publicado: (2022)

Chest radiograph of an asymptomatic man
por: Chaini, Eleftheria, et al.
Publicado: (2016)

Gold Threads on Chest Radiograph
por: Kajihara, Yusaku
Publicado: (2022)

Individual differences in perceptual abilities in medical imaging: the Vanderbilt Chest Radiograph Test
por: Sunday, Mackenzie A., et al.
Publicado: (2017)

Annotating digital text with phonemic cues to support decoding in struggling readers
por: Donnelly, Patrick M., et al.
Publicado: (2020)

Deep-learning convolutional neural networks with transfer learning accurately classify COVID-19 lung infection on portable chest radiographs
por: Kikkisetti, Shreeja, et al.
Publicado: (2020)

Retracted: The Use of Chest Radiographs and Machine Learning Model for the Rapid Detection of Pneumonitis in Pediatric
por: International, BioMed Research
Publicado: (2023)

Comparing image analysis approaches versus expert readers: the relation of knee radiograph features to knee pain
por: Minciullo, Luca, et al.
Publicado: (2018)

Chest radiograph in subclavian vein cannulation
por: Abbas, Haider, et al.
Publicado: (2011)

Unusual Cause of Chest Pain on Radiograph
por: Gallitelli, Mauro, et al.
Publicado: (2011)

Why intensivists want chest radiographs
por: Tolsma, Martijn, et al.
Publicado: (2015)

Chest radiographic manifestations of scrub typhus
por: Abhilash, KPP, et al.
Publicado: (2016)

Validation of deep learning-based computer-aided detection software use for interpretation of pulmonary abnormalities on chest radiographs and examination of factors that influence readers’ performance and final diagnosis
por: Toda, Naoki, et al.
Publicado: (2022)

Classified and Annotated Bibliography of Sir William Osler's Publications
por: Smith, G. H.
Publicado: (1939)

Classified and Annotated Bibliography of Sir William Osler’s Publications
Publicado: (1939)

Cannot write session to /tmp/vufind_sessions/sess_rnk4up2ffbtud124dkrdhkpfds