Prediction of progression in idiopathic pulmonary fibrosis using CT scans at baseline: A quantum particle swarm optimization - Random forest approach-Reference-Cited by-同舟云学术

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Prediction of progression in idiopathic pulmonary fibrosis using CT scans at baseline: A quantum particle swarm optimization - Random forest approach

Published:2019-09 Issue: Volume:100 Page:101709
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Shi Yu,Wong Weng Kee,Goldin Jonathan G.,Brown Matthew S.,Kim Grace Hyun J.

Funder

National Heart, Lung, and Blood Institute of the National Institutes of Health

National Institute of General Medical Sciences

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference66 articles.

1. Idiopathic pulmonary fibrosis in us medicare beneficiaries aged 65 years and older: incidence, prevalence, and survival, 2001–11;Raghu;Lancet Respir Med,2014

2. An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management;Raghu;Am J Respir Crit Care Med,2011

3. FG-3019 anti-connective tissue growth factor monoclonal antibody: results of an open-label clinical trial in idiopathic pulmonary fibrosis;Raghu;Eur Respir J,2016

4. Fibroblastic foci in usual interstitial pneumonia: idiopathic versus collagen vascular disease;Flaherty;Am J Respir Crit Care Med,2003

5. Computer recognition of regional lung disease patterns;Uppaluri;Am J Respir Crit Care Med,1999

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1. ELIPF: Explicit Learning Framework for Pre-Emptive Forecasting, Early Detection and Curtailment of Idiopathic Pulmonary Fibrosis Disease;BioMedInformatics;2024-08-01

2. Optimal designs for nonlinear mixed-effects models using competitive swarm optimizer with mutated agents;Statistics and Computing;2024-07-17

3. Chest X-ray Images for Lung Disease Detection Using Deep Learning Techniques: A Comprehensive Survey;Archives of Computational Methods in Engineering;2024-02-19

4. Analysis of Validation Performance of a Machine Learning Classifier in Interstitial Lung Disease Cases Without Definite or Probable Usual Interstitial Pneumonia Pattern on CT Using Clinical and Pathology-Supported Diagnostic Labels;Journal of Imaging Informatics in Medicine;2024-01-11

5. Predictive analysis of pulmonary fibrosis progression using gradient boosting classifier and DICOM images;AIP Conference Proceedings;2024

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