ArticleRadiology. Artificial intelligence2021
Deep Learning Systems for Pneumothorax Detection on Chest Radiographs: A Multicenter External Validation Study.
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21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The diagnostic value of radiomics-based machine learning for lymph node metastasis in prostate cancer: a systematic review and meta-analysis.Frontiers in oncology · 2026Pooled it
- Deep learning for pneumothorax diagnosis: a systematic review and meta-analysis.European respiratory review : an official journal of the European Respiratory Society · 2023Pooled it
- Large-scale evaluation of multimodal large language models for pneumothorax detection.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Article
- Severe trauma care: advances and future directions in diagnostic and therapeutic techniques and information technology support.Medical review (2021) · 2026Article
- Artificial Intelligence in Pleural Diseases: Current Applications and Next Steps.Thoracic research and practice · 2026Article
- PulmoX-Net: a channel-attention enhanced deep learning model for multi-class pulmonary pathology classification in chest radiography.Frontiers in medicine · 2026Article
- Evaluation of the effectiveness of the ChatGPT artificial intelligence application in the diagnosis of spontaneous pneumothorax on chest radiograph interpretation.BMC pulmonary medicine · 2025Article
- Impact of AI Assistance in Pneumothorax Detection on Chest Radiographs Among Readers of Varying Experience.Diagnostics (Basel, Switzerland) · 2025Article
- Subgroup evaluation to understand performance gaps in deep learning-based classification of regions of interest on mammography.PLOS digital health · 2025Article
- Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would.Frontiers in physiology · 2025Article
- Leveraging anatomical constraints with uncertainty for pneumothorax segmentation.Health care science · 2024Article
- Utilizing ChatGPT for Curriculum Learning in Developing a Clinical Grade Pneumothorax Detection Model: A Multisite Validation Study.Journal of clinical medicine · 2024Article
- Data mining approaches to pneumothorax detection: Integrating mask-RCNN and medical transfer learning techniques.MethodsX · 2024Article
- The Subgroup Imperative: Chest Radiograph Classifier Generalization Gaps in Patient, Setting, and Pathology Subgroups.Radiology. Artificial intelligence · 2023Article
- AI-based radiodiagnosis using chest X-rays: A review.Frontiers in big data · 2023Review
- Performance of a Chest Radiography AI Algorithm for Detection of Missed or Mislabeled Findings: A Multicenter Study.Diagnostics (Basel, Switzerland) · 2022Article
- Recent Advances in Molecular Diagnosis of Pulmonary Fibrosis for Precision Medicine.ACS pharmacology & translational science · 2022Review
- Localization-adjusted diagnostic performance and assistance effect of a computer-aided detection system for pneumothorax and consolidation.NPJ digital medicine · 2022Article
- Diagnostic accuracy of a commercially available deep-learning algorithm in supine chest radiographs following trauma.The British journal of radiology · 2022Article
- External validation based on transfer learning for diagnosing atelectasis using portable chest X-rays.Frontiers in medicine · 2022Article
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12 authors.
Yee Liang ThianDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).ORCID https://orcid.org/0000-0001-9899-205X
Dianwen NgDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).
James Thomas Patrick Decourcy HallinanDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).
Pooja JagmohanDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).ORCID https://orcid.org/0000-0001-8491-0375
Soon Yiew SiaDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).ORCID https://orcid.org/0000-0002-8609-9587
Cher Heng TanDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).
Yong Han TingDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).ORCID https://orcid.org/0000-0002-8682-9914
Pin Lin KeiDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).ORCID https://orcid.org/0000-0003-1349-8058
Geoiphy George PulickalDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).ORCID https://orcid.org/0000-0002-2498-859X
Vincent Tze Yang TiongDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).ORCID https://orcid.org/0000-0002-6433-8815
Swee Tian QuekDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).ORCID https://orcid.org/0000-0001-7561-7492
Mengling FengDepartment of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074 (Y.L.T., D.N., J.T.P.D.H., P.J., S.Y.S., V.T.Y.T., S.T.Q.); Saw Swee Hock School of Public Health, School of Computer Science, and Yong Loo Lin School of Medicine, National University of Singapore, Singapore (D.N., M.F.); Department of Diagnostic Radiology, Alexandra Hospital, Singapore (J.T.P.D.H.); Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore (C.H.T., Y.H.T.); Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore (C.H.T.); Department of Diagnostic Radiology, Ng Teng Fong General Hospital, Singapore (P.L.K.); and Department of Diagnostic Radiology, Khoo Teck Puat Hospital, Singapore (G.G.P.).ORCID https://orcid.org/0000-0002-5338-6248
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo assess the generalizability of a deep learning pneumothorax detection model on datasets from multiple external institutions and examine patient and acquisition factors that might influence performance. MATERIALS AND
methodsIn this retrospective study, a deep learning model was trained for pneumothorax detection by merging two large open-source chest radiograph datasets: ChestX-ray14 and CheXpert. It was then tested on six external datasets from multiple independent institutions (labeled A-F) in a retrospective case-control design (data acquired between 2016 and 2019 from institutions A-E; institution F consisted of data from the MIMIC-CXR dataset). Performance on each dataset was evaluated by using area under the receiver operating characteristic curve (AUC) analysis, sensitivity, specificity, and positive and negative predictive values, with two radiologists in consensus being used as the reference standard. Patient and acquisition factors that influenced performance were analyzed.
resultsThe AUCs for pneumothorax detection for external institutions A-F were 0.91 (95% CI: 0.88, 0.94), 0.97 (95% CI: 0.94, 0.99), 0.91 (95% CI: 0.85, 0.97), 0.98 (95% CI: 0.96, 1.0), 0.97 (95% CI: 0.95, 0.99), and 0.92 (95% CI: 0.90, 0.95), respectively, compared with the internal test AUC of 0.93 (95% CI: 0.92, 0.93). The model had lower performance for small compared with large pneumothoraces (AUC, 0.88 [95% CI: 0.85, 0.91] vs AUC, 0.96 [95% CI: 0.95, 0.97];
conclusionA deep learning model trained with a large volume of data on the task of pneumothorax detection was able to generalize well to multiple external datasets with patient demographics and technical parameters independent of the training data.
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Computer Applications-Detection/DiagnosisThorax
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