ArticleDiagnostics (Basel, Switzerland)2024
A Machine Learning System to Indicate Diagnosis of Idiopathic Pulmonary Fibrosis Non-Invasively in Challenging Cases.
Article in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 8 citations in OpenAlex.
- Clinical Utility of an FDA-Authorized Artificial Intelligence Imaging Platform in Interstitial Lung Disease Diagnosis.Diagnostics (Basel, Switzerland) · 2026Article
- Paired Validation of a Multimodal Vision-Transformer System for the Non-Invasive Diagnosis of Idiopathic Pulmonary Fibrosis.Diagnostics (Basel, Switzerland) · 2026Article
- A systematic review of artificial intelligence-based diagnosis models for idiopathic pulmonary fibrosis.Journal of thoracic disease · 2026Review
- Advances in diagnosis of lung fibrosis: focus on present and future approaches.Frontiers in medicine · 2026Review
- Artificial intelligence in idiopathic pulmonary fibrosis: advances, challenges and future directions.The European respiratory journal · 2026Review
- Deep-learning-based 3D content-based image retrieval system on chest HRCT: Performance assessment for interstitial lung diseases and usual interstitial pneumonia.European journal of radiology open · 2025Article
- Fibrotic Hypersensitivity Pneumonitis: A Diagnostic Challenge Leading to Lung Transplantation.Diagnostics (Basel, Switzerland) · 2025Article
- [Research Progress of Anti-lung Cancer Drug-related Interstitial Lung Disease].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025Review
- Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data.BMC pulmonary medicine · 2024Article
- 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 · 2024Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiologic usual interstitial pneumonia (UIP) patterns and concordant clinical characteristics define a diagnosis of idiopathic pulmonary fibrosis (IPF). However, limited expert access and high inter-clinician variability challenge early and pre-invasive diagnostic sensitivity and differentiation of IPF from other interstitial lung diseases (ILDs). We investigated a machine learning-driven software system, Fibresolve, to indicate IPF diagnosis in a heterogeneous group of 300 patients with interstitial lung disease work-up in a retrospective analysis of previously and prospectively collected registry data from two US clinical sites. Fibresolve analyzed cases at the initial pre-invasive assessment. An Expert Clinical Panel (ECP) and three panels of clinicians with varying experience analyzed the cases for comparison. Ground Truth was defined by separate multi-disciplinary discussion (MDD) with the benefit of surgical pathology results and follow-up. Fibresolve met both pre-specified co-primary endpoints of sensitivity superior to ECP and significantly greater specificity (
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