{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:50:45Z","timestamp":1792785045510,"version":"4.5.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T00:00:00Z","timestamp":1781913600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"vor","delay-in-days":101,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"The Beijing Municipal Science & Technology Commission","award":["No. L232125"],"award-info":[{"award-number":["No. L232125"]}],"id":[{"id":"https:\/\/ror.org\/034k14f91","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-57793-8","type":"journal-article","created":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T08:13:59Z","timestamp":1781943239000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A machine learning model for predicting pneumothorax risk after computed tomography-guided percutaneous transthoracic needle biopsy: A two-hospital retrospective study"],"prefix":"10.1038","volume":"16","author":[{"given":"Fangfang","family":"Tian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Libao","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiying","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haipeng","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,20]]},"reference":[{"key":"57793_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.canep.2024.102693","volume":"93","author":"J Zhou","year":"2024","unstructured":"Zhou, J. et al. Global burden of lung cancer in 2022 and projections to 2050: Incidence and mortality estimates from GLOBOCAN. Cancer. Epidemiol. 93, 102693 (2024).","journal-title":"Cancer. Epidemiol."},{"issue":"1127","key":"57793_CR2","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.20210065","volume":"94","author":"J Kim","year":"2021","unstructured":"Kim, J., Chee, C. G., Cho, J., Kim, Y. & Yoon, M. A. Diagnostic accuracy and complication rate of image-guided percutaneous transthoracic needle lung biopsy for subsolid pulmonary nodules: A systematic review and meta-analysis. Br. J. Radiol. 94(1127), 20210065 (2021).","journal-title":"Br. J. Radiol."},{"issue":"1","key":"57793_CR3","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.243593","volume":"317","author":"K Ahrar","year":"2025","unstructured":"Ahrar, K. How I do it: CT-guided percutaneous transthoracic lung biopsy. Radiology. 317(1), e243593 (2025).","journal-title":"Radiology."},{"key":"57793_CR4","unstructured":"Young M, Sankari A: Percutaneous Lung Lesion Biopsy. In: StatPearls. edn. Treasure Island (FL): StatPearls PublishingCopyright \u00a9 2025, StatPearls Publishing LLC.; (2025)."},{"issue":"4","key":"57793_CR5","doi-asserted-by":"publisher","first-page":"534","DOI":"10.5152\/dir.2021.20042","volume":"27","author":"J Zhu","year":"2021","unstructured":"Zhu, J., Wang, X., Qu, Y. & Wen, Z. CT-guided core needle biopsy of the lung in patients with primary malignancy suspected of lung metastasis: 5-year experience from a single institution. Diagn. Interv. Radiol. 27(4), 534\u2013541 (2021).","journal-title":"Diagn. Interv. Radiol."},{"issue":"1","key":"57793_CR6","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1148\/radiol.2015150381","volume":"279","author":"R Tai","year":"2016","unstructured":"Tai, R. et al. Frequency and severity of pulmonary hemorrhage in patients undergoing percutaneous CT-guided transthoracic lung biopsy: Single-institution experience of 1175 cases. Radiology. 279(1), 287\u2013296 (2016).","journal-title":"Radiology."},{"issue":"6","key":"57793_CR7","doi-asserted-by":"publisher","first-page":"W678","DOI":"10.2214\/AJR.10.4659","volume":"196","author":"CC Wu","year":"2011","unstructured":"Wu, C. C., Maher, M. M. & Shepard, J. A. Complications of CT-guided percutaneous needle biopsy of the chest: prevention and management. AJR. Am. J. Roentgenol. 196(6), W678-682 (2011).","journal-title":"AJR. Am. J. Roentgenol."},{"issue":"3","key":"57793_CR8","doi-asserted-by":"publisher","first-page":"1328","DOI":"10.1007\/s00330-017-5058-7","volume":"28","author":"WH Lim","year":"2018","unstructured":"Lim, W. H. et al. Time-dependent analysis of incidence, risk factors and clinical significance of pneumothorax after percutaneous lung biopsy. Eur. Radiol. 28(3), 1328\u20131337 (2018).","journal-title":"Eur. Radiol."},{"issue":"7","key":"57793_CR9","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1016\/j.jvir.2010.01.011","volume":"21","author":"S Gupta","year":"2010","unstructured":"Gupta, S. et al. Quality improvement guidelines for percutaneous needle biopsy. J. Vasc. Interv. Radiol. 21(7), 969\u2013975 (2010).","journal-title":"J. Vasc. Interv. Radiol."},{"issue":"11","key":"57793_CR10","doi-asserted-by":"publisher","first-page":"1530","DOI":"10.1111\/1759-7714.12849","volume":"9","author":"Z Guo","year":"2018","unstructured":"Guo, Z. et al. Chinese multidisciplinary expert consensus: guidelines on percutaneous transthoracic needle biopsy. Thoracic. Cancer. 9(11), 1530\u20131543 (2018).","journal-title":"Thoracic. Cancer."},{"key":"57793_CR11","doi-asserted-by":"publisher","DOI":"10.3390\/jcm14144867","author":"RA Pugliesi","year":"2025","unstructured":"Pugliesi, R. A. et al. Reevaluating routine post-biopsy chest X-rays after CT-guided lung biopsy: incidence of pneumothorax and value of symptom-based monitoring. J. of Clin. Med. https:\/\/doi.org\/10.3390\/jcm14144867 (2025).","journal-title":"J. of Clin. Med."},{"key":"57793_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2021.109749","volume":"140","author":"L Yang","year":"2021","unstructured":"Yang, L. et al. Nomogram model to predict pneumothorax after computed tomography-guided coaxial core needle lung biopsy. Euro. J. Radiology. 140, 109749 (2021).","journal-title":"Euro. J. Radiology."},{"issue":"1","key":"57793_CR13","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","volume":"58","author":"R Tibshirani","year":"1996","unstructured":"Tibshirani, R. Regression shrinkage and selection via the lasso. J. Roy. Stat. Soc. Ser. B. Stat. Method. 58(1), 267\u2013288 (1996).","journal-title":"J. Roy. Stat. Soc. Ser. B. Stat. Method."},{"issue":"9","key":"57793_CR14","doi-asserted-by":"publisher","first-page":"2172","DOI":"10.1007\/s12094-024-03413-8","volume":"26","author":"D Elkahwagy","year":"2024","unstructured":"Elkahwagy, D., Kiriacos, C. J. & Mansour, M. Logistic regression and other statistical tools in diagnostic biomarker studies. Clin. Transl. Oncol. 26(9), 2172\u20132180 (2024).","journal-title":"Clin. Transl. Oncol."},{"issue":"1","key":"57793_CR15","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.hcl.2025.08.003","volume":"42","author":"JA Pruneski","year":"2026","unstructured":"Pruneski, J. A. & Pareek, A. Support Vector machines: techniques and applications. Hand. Clin. 42(1), 19\u201325 (2026).","journal-title":"Hand. Clin."},{"issue":"6","key":"57793_CR16","doi-asserted-by":"publisher","first-page":"894","DOI":"10.1016\/j.ajodo.2023.09.011","volume":"164","author":"T Becker","year":"2023","unstructured":"Becker, T., Rousseau, A. J., Geubbelmans, M., Burzykowski, T. & Valkenborg, D. Decision trees and random forests. Am. J. Orthod. Dentofacial. Orthop. 164(6), 894\u2013897 (2023).","journal-title":"Am. J. Orthod. Dentofacial. Orthop."},{"issue":"7","key":"57793_CR17","doi-asserted-by":"publisher","first-page":"3156","DOI":"10.1109\/TNNLS.2020.3009776","volume":"32","author":"Z Zhang","year":"2021","unstructured":"Zhang, Z. & Jung, C. GBDT-MO: gradient-boosted decision trees for multiple outputs. IEEE Trans. Neural. Netw. Learn. Syst. 32(7), 3156\u20133167 (2021).","journal-title":"IEEE Trans. Neural. Netw. Learn. Syst."},{"key":"57793_CR18","unstructured":"Ke G, Meng Q, Finley T, Wang T, Chen W, Ma W, Ye Q, Liu T-Y: LightGBM: a highly efficient gradient boosting decision tree. In: Proc. of the 31st International Conference on Neural Information Processing Systems. Long Beach, California, USA: Curran Associates Inc. 3149 3157. (2017)."},{"issue":"7","key":"57793_CR19","first-page":"536","volume":"120","author":"V Renganathan","year":"2019","unstructured":"Renganathan, V. Overview of artificial neural network models in the biomedical domain. Bratisl. Lek. Listy. 120(7), 536\u2013540 (2019).","journal-title":"Bratisl. Lek. Listy."},{"key":"57793_CR20","volume":"4","author":"SK Kiangala","year":"2021","unstructured":"Kiangala, S. K. & Wang, Z. An effective adaptive customization framework for small manufacturing plants using extreme gradient boosting-XGBoost and random forest ensemble learning algorithms in an Industry 4.0 environment. Mach. Learn. Appl. 4, 100024 (2021).","journal-title":"Mach. Learn. Appl."},{"issue":"7","key":"57793_CR21","doi-asserted-by":"publisher","first-page":"07TR01","DOI":"10.1088\/1361-6560\/aab4b1","volume":"63","author":"NA Obuchowski","year":"2018","unstructured":"Obuchowski, N. A. & Bullen, J. A. Receiver operating characteristic (ROC) curves: Review of methods with applications in diagnostic medicine. Phys. in Med. Biol. 63(7), 07TR01 (2018).","journal-title":"Phys. in Med. Biol."},{"key":"57793_CR22","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.prevetmed.2017.11.018","volume":"149","author":"C Fenlon","year":"2018","unstructured":"Fenlon, C., O\u2019Grady, L., Doherty, M. L. & Dunnion, J. A discussion of calibration techniques for evaluating binary and categorical predictive models. Prev. Vet. Med. 149, 107\u2013114 (2018).","journal-title":"Prev. Vet. Med."},{"issue":"15","key":"57793_CR23","doi-asserted-by":"publisher","first-page":"308","DOI":"10.21037\/atm.2018.07.02","volume":"6","author":"Z Zhang","year":"2018","unstructured":"Zhang, Z. et al. Decision curve analysis: a technical note. Ann. Transl. Med. 6(15), 308 (2018).","journal-title":"Ann. Transl. Med."},{"key":"57793_CR24","unstructured":"Lundberg SM, Lee S-I: A unified approach to interpreting model predictions. Advances in neural information processing systems 30 (2017)."},{"issue":"8","key":"57793_CR25","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1016\/j.amjmed.2020.03.033","volume":"133","author":"S Ellahham","year":"2020","unstructured":"Ellahham, S. Artificial intelligence: the future for diabetes care. Am. J. Med. 133(8), 895\u2013900 (2020).","journal-title":"Am. J. Med."},{"issue":"1","key":"57793_CR26","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1016\/j.numecd.2023.08.018","volume":"34","author":"S Mohseni-Takalloo","year":"2024","unstructured":"Mohseni-Takalloo, S., Mozaffari-Khosravi, H., Mohseni, H., Mirzaei, M. & Hosseinzadeh, M. Metabolic syndrome prediction using non-invasive and dietary parameters based on a support vector machine. Nutr. Metab. Cardiovasc. Dis. 34(1), 126\u2013135 (2024).","journal-title":"Nutr. Metab. Cardiovasc. Dis."},{"issue":"6","key":"57793_CR27","doi-asserted-by":"publisher","first-page":"666","DOI":"10.1177\/02841851251322070","volume":"66","author":"A Turkar","year":"2025","unstructured":"Turkar, A., Baysal, T., Dumlu, T. R. & Dizman, R. Factors affecting the development of pneumothorax in transthoracic fine-needle aspiration biopsies. Acta. Radiol. 66(6), 666\u2013674 (2025).","journal-title":"Acta. Radiol."},{"key":"57793_CR28","doi-asserted-by":"publisher","DOI":"10.3390\/geriatrics9020034","author":"PR Joshi","year":"2024","unstructured":"Joshi, P. R. Pulmonary diseases in older patients: Understanding and addressing the challenges. Geriatrics. https:\/\/doi.org\/10.3390\/geriatrics9020034 (2024).","journal-title":"Geriatrics."},{"issue":"10","key":"57793_CR29","doi-asserted-by":"publisher","DOI":"10.3390\/ijms24108725","volume":"24","author":"S Kotlyarov","year":"2023","unstructured":"Kotlyarov, S. The role of smoking in the mechanisms of development of chronic obstructive pulmonary disease and atherosclerosis. Intern. J. Mol. Sci. 24(10), 8725 (2023).","journal-title":"Intern. J. Mol. Sci."},{"key":"57793_CR30","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.semcancer.2022.09.001","volume":"86","author":"A Comandatore","year":"2022","unstructured":"Comandatore, A. et al. Lactate Dehydrogenase and its clinical significance in pancreatic and thoracic cancers. Sem. in Cancer. Bio. 86, 93\u2013100 (2022).","journal-title":"Sem. in Cancer. Bio."},{"issue":"6","key":"57793_CR31","doi-asserted-by":"publisher","first-page":"3559","DOI":"10.21037\/jtd-2024-2286","volume":"17","author":"J Wu","year":"2025","unstructured":"Wu, J. et al. A nomogram model for predicting pneumothorax after CT-guided localization of pulmonary nodules using autologous blood and methylene blue. J. Thorac. Dis. 17(6), 3559\u20133567 (2025).","journal-title":"J. Thorac. Dis."},{"key":"57793_CR32","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2025.1605797","volume":"16","author":"G Jia","year":"2025","unstructured":"Jia, G., Song, E., Zheng, Z., Qian, M. & Liu, G. Alveolar epithelial cells in bacterial sepsis-associated acute lung injury: mechanisms and therapeutic strategies. Front. Immunol. 16, 1605797 (2025).","journal-title":"Front. Immunol."},{"issue":"3","key":"57793_CR33","doi-asserted-by":"publisher","first-page":"209","DOI":"10.5472\/marumj.1798655","volume":"38","author":"B \u00d6zdemir","year":"2025","unstructured":"\u00d6zdemir, B. & S\u00f6nmez, D. Association between the geriatric nutritional risk index and the development of pneumothorax after CT-guided transthoracic lung biopsy. Marmara. Medical. J. 38(3), 209\u2013214 (2025).","journal-title":"Marmara. Medical. J."},{"issue":"1","key":"57793_CR34","volume":"8","author":"Y Li","year":"2023","unstructured":"Li, Y. et al. Diabetic vascular diseases: molecular mechanisms and therapeutic strategies. Sign. Trans. Tar. Therapy 8(1), 152 (2023).","journal-title":"Sign. Trans. Tar. Therapy"},{"issue":"1","key":"57793_CR35","doi-asserted-by":"publisher","DOI":"10.1186\/s41512-024-00177-1","volume":"8","author":"L Barre\u00f1ada","year":"2024","unstructured":"Barre\u00f1ada, L., Dhiman, P., Timmerman, D., Boulesteix, A.-L. & Van Calster, B. Understanding overfitting in random forest for probability estimation: a visualization and simulation study. Diagno. Progno. Res. 8(1), 14 (2024).","journal-title":"Diagno. Progno. Res."},{"issue":"3","key":"57793_CR36","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1097\/LBR.0000000000000816","volume":"29","author":"T Sargent","year":"2022","unstructured":"Sargent, T., Kolderman, N., Nair, G. B., Jankowski, M. & Al-Katib, S. Risk factors for pneumothorax development following CT-guided core lung nodule biopsy. J. Bron. Inter. Pulmon. 29(3), 198\u2013205 (2022).","journal-title":"J. Bron. Inter. Pulmon."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-57793-8","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-57793-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-57793-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T22:36:42Z","timestamp":1790635002000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-57793-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,20]]},"references-count":36,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["57793"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-57793-8","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,20]]},"assertion":[{"value":"3 April 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 June 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no conflicts of interest. The funders had no role in the study\u2019s design, collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.","order":1,"name":"Ethics","label":"Competing of interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"30110"}}