{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T22:01:33Z","timestamp":1793311293422,"version":"4.5.0"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T00:00:00Z","timestamp":1766534400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T00:00:00Z","timestamp":1768348800000},"content-version":"vor","delay-in-days":21,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-025-31432-0","type":"journal-article","created":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T08:34:05Z","timestamp":1766565245000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["An efficient hybrid artificial intelligence framework for lung cancer classification using CT images"],"prefix":"10.1038","volume":"16","author":[{"given":"L.","family":"Kamala","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K. G.","family":"Mohan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,12,24]]},"reference":[{"issue":"3","key":"31432_CR1","doi-asserted-by":"publisher","first-page":"288","DOI":"10.21037\/tlcr.2016.06.07","volume":"5","author":"C Zappa","year":"2016","unstructured":"Zappa, C. & Mousa, S. A. Non-small cell lung cancer: Current treatment and future advances. Transl. Lung Cancer Res. 5(3), 288 (2016).","journal-title":"Transl. Lung Cancer Res."},{"issue":"1","key":"31432_CR2","first-page":"92","volume":"11","author":"S Dash","year":"2025","unstructured":"Dash, S., Padhy, S., Suman, P. & Das, R. K. Enhancing lung cancer diagnosis through CT scan image analysis using mask-EffNet. Eng. Access 11(1), 92\u2013107 (2025).","journal-title":"Eng. Access"},{"key":"31432_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105373","volume":"88","author":"N Venkatesan","year":"2024","unstructured":"Venkatesan, N., Pasupathy, S. & Gobinathan, B. An efficient lung cancer detection using optimal SVM and improved weight-based beetle swarm optimization. Biomed. Signal Process. Control 88, 105373 (2024).","journal-title":"Biomed. Signal Process. Control"},{"key":"31432_CR4","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1007\/s00330-005-0010-7","volume":"16","author":"HJ Williams","year":"2006","unstructured":"Williams, H. J. & Davies, A. M. The effect of X-rays on bone: A pictorial review. Eur. Radiol. 16, 619\u2013633 (2006).","journal-title":"Eur. Radiol."},{"key":"31432_CR5","doi-asserted-by":"publisher","first-page":"100357","DOI":"10.1016\/j.array.2024.100357","volume":"23","author":"MN Yeasmin","year":"2024","unstructured":"Yeasmin, M. N., Al Amin, M., Joti, T. J., Aung, Z. & Azim, M. A. Advances of AI in image-based computer-aided diagnosis: A review. Array 23, 100357 (2024).","journal-title":"Array"},{"issue":"2","key":"31432_CR6","doi-asserted-by":"publisher","first-page":"266","DOI":"10.37917\/ijeee.20.2.23","volume":"20","author":"AM Qadir","year":"2024","unstructured":"Qadir, A. M., Abdalla, P. A. & Abd, D. F. A hybrid lung cancer model for diagnosis and stage classification from computed tomography images. Iraqi J. Electr. Electr. Eng. 20(2), 266\u2013274 (2024).","journal-title":"Iraqi J. Electr. Electr. Eng."},{"key":"31432_CR7","first-page":"100203","volume":"11","author":"AA Abe","year":"2025","unstructured":"Abe, A. A. et al. A robust deep learning algorithm for lung cancer detection from computed tomography images. Intell.-Based Med. 11, 100203 (2025).","journal-title":"Intell.-Based Med."},{"issue":"1","key":"31432_CR8","doi-asserted-by":"publisher","first-page":"41","DOI":"10.33093\/jiwe.2024.3.1.3","volume":"3","author":"CC Chiet","year":"2024","unstructured":"Chiet, C. C., How, K. W., Han, P. Y. & Yen, Y. H. A lung cancer detection with pre-trained CNN models. J. Inform. Web Eng. 3(1), 41\u201354 (2024).","journal-title":"J. Inform. Web Eng."},{"issue":"1","key":"31432_CR9","doi-asserted-by":"publisher","first-page":"2039","DOI":"10.32604\/cmc.2023.032927","volume":"74","author":"I Naseer","year":"2023","unstructured":"Naseer, I. et al. Lung cancer detection using modified AlexNet architecture and support vector machine. Comput. Mater. Continua 74(1), 2039\u20132054 (2023).","journal-title":"Comput. Mater. Continua"},{"issue":"1","key":"31432_CR10","doi-asserted-by":"publisher","first-page":"2987","DOI":"10.1038\/s41598-023-29656-z","volume":"13","author":"AA Shah","year":"2023","unstructured":"Shah, A. A., Malik, H. A. M., Muhammad, A., Alourani, A. & Butt, Z. A. Deep learning ensemble 2D CNN approach towards the detection of lung cancer. Sci. Rep. 13(1), 2987 (2023).","journal-title":"Sci. Rep."},{"key":"31432_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105319","volume":"86","author":"C Yan","year":"2023","unstructured":"Yan, C. & Razmjooy, N. Optimal lung cancer detection based on CNN optimized and improved Snake optimization algorithm. Biomed. Signal Process. Control 86, 105319 (2023).","journal-title":"Biomed. Signal Process. Control"},{"key":"31432_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.health.2023.100150","volume":"3","author":"N Maleki","year":"2023","unstructured":"Maleki, N. & Akhavan Niaki, S. T. An intelligent algorithm for lung cancer diagnosis using extracted features from computerized tomography images. Healthc. Anal. 3, 100150 (2023).","journal-title":"Healthc. Anal."},{"issue":"1","key":"31432_CR13","doi-asserted-by":"publisher","first-page":"99","DOI":"10.3390\/diagnostics13010099","volume":"13","author":"C Melo-Alvim","year":"2022","unstructured":"Melo-Alvim, C. et al. Radiotherapy, chemotherapy and immunotherapy\u2014current practice and future perspectives for recurrent\/metastatic oral cavity squamous cell carcinoma. Diagnostics 13(1), 99 (2022).","journal-title":"Diagnostics"},{"issue":"1","key":"31432_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.14316\/pmp.2021.32.1.1","volume":"32","author":"H Jung","year":"2021","unstructured":"Jung, H. Basic physical principles and clinical applications of computed tomography. Progress Med. Phys. 32(1), 1\u201317 (2021).","journal-title":"Progress Med. Phys."},{"issue":"2","key":"31432_CR15","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/s42979-022-01606-y","volume":"4","author":"S Avinash","year":"2023","unstructured":"Avinash, S., Naveen Kumar, H. N., Guru Prasad, M. S., Mohan Naik, R. & Parveen, G. Early detection of malignant tumor in lungs using feed-forward neural network and K-nearest neighbor classifier. SN Comput. Sci. 4(2), 195 (2023).","journal-title":"SN Comput. Sci."},{"key":"31432_CR16","doi-asserted-by":"crossref","unstructured":"Mamun, M.; Mahmud, M. I.; Meherin, M.; Abdelgawad, A. LCDctCNN: Lung cancer diagnosis of CT scan images using CNN based model. In 2023 10th International Conference on Signal Processing and Integrated Networks (SPIN), 205\u2013212, IEEE, 2023.","DOI":"10.1109\/SPIN57001.2023.10116075"},{"key":"31432_CR17","unstructured":"Al-Yasriy, H. F. The IQ-OTH\/NCCD Lung Cancer Dataset (Kaggle, 2023)."},{"issue":"5","key":"31432_CR18","doi-asserted-by":"publisher","first-page":"2332","DOI":"10.3390\/app11052332","volume":"11","author":"S Barburiceanu","year":"2021","unstructured":"Barburiceanu, S., Terebes, R. & Meza, S. 3D texture feature extraction and classification using GLCM and LBP-based descriptors. Appl. Sci. 11(5), 2332 (2021).","journal-title":"Appl. Sci."},{"issue":"5","key":"31432_CR19","first-page":"1","volume":"3","author":"P Mohanaiah","year":"2013","unstructured":"Mohanaiah, P., Sathyanarayana, P. & GuruKumar, L. Image texture feature extraction using GLCM approach. Int. J. Sci. Res. Publ. 3(5), 1\u20135 (2013).","journal-title":"Int. J. Sci. Res. Publ."},{"key":"31432_CR20","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-0853-0","volume-title":"Texture Feature Extraction Techniques for Image Recognition","author":"J Chaki","year":"2020","unstructured":"Chaki, J. & Dey, N. Texture Feature Extraction Techniques for Image Recognition (Springer, 2020)."},{"key":"31432_CR21","doi-asserted-by":"crossref","unstructured":"Burger, W. & Burge, M. J. Scale-invariant feature transform (SIFT). In Digital Image Processing: An Algorithmic Introduction 709\u2013763 (Springer, 2022).","DOI":"10.1007\/978-3-031-05744-1_25"},{"key":"31432_CR22","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1023\/A:1008045108935","volume":"30","author":"T Lindeberg","year":"1998","unstructured":"Lindeberg, T. Feature detection with automatic scale selection. Int. J. Comput. Vision 30, 79\u2013116 (1998).","journal-title":"Int. J. Comput. Vision"},{"issue":"September","key":"31432_CR23","first-page":"398","volume":"4","author":"M Brown","year":"2002","unstructured":"Brown, M. & Lowe, D. G. Invariant features from interest point groups. In BMVC 4(September), 398\u2013410 (2002).","journal-title":"In BMVC"},{"key":"31432_CR24","unstructured":"Simonyan, K.; Zisserman, A. Very deep convolutional networks for large-scale image recognition. https:\/\/arxiv.org\/abs\/1409.1556 (2014)."},{"key":"31432_CR25","doi-asserted-by":"crossref","unstructured":"Tao, J., Gu, Y., Sun, J., Bie, Y. & Wang, H. Research on VGG16 convolutional neural network feature classification algorithm based on Transfer Learning. In 2021 2nd China International SAR Symposium (CISS) 1\u20133 (IEEE, 2021).","DOI":"10.23919\/CISS51089.2021.9652277"},{"key":"31432_CR26","unstructured":"Howard, A. G. et al. Mobilenets: Efficient convolutional neural networks for mobile vision applications. https:\/\/arxiv.org\/abs\/1409.1556 (2017)."},{"key":"31432_CR27","doi-asserted-by":"crossref","unstructured":"Sinha, D., El-Sharkawy, M. Thin MobileNet: An enhanced MobileNet architecture. In 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) 280\u2013285 (IEEE, 2019).","DOI":"10.1109\/UEMCON47517.2019.8993089"},{"key":"31432_CR28","unstructured":"Abdollahi, J. Evaluating LeNet algorithms in classification lung cancer from Iraq-oncology teaching hospital\/national center for cancer diseases. Preprint at https:\/\/arxiv.org\/abs\/2305.13333 (2023)."},{"key":"31432_CR29","unstructured":"Talukder, M. A. R., Singho, A. P., Mia, M. M., Jahan, N. & Islam, M. R. Unveiling hidden lesions: A deep dive into deep learning advancements for lung cancer imaging analysis. Thesis (AIUB, 2024)."},{"issue":"3","key":"31432_CR30","first-page":"63","volume":"10","author":"B Mostafa","year":"2023","unstructured":"Mostafa, B., Keshk, A. & Sakr, M. A deep-learning model based on transfer-learning technique for detecting and classifying anomalies in lungs images. Int. J. Comput. Inf. 10(3), 63\u201372 (2023).","journal-title":"Int. J. Comput. Inf."},{"issue":"8","key":"31432_CR31","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0285796","volume":"18","author":"TIA Mohamed","year":"2023","unstructured":"Mohamed, T. I. A., Oyelade, O. N. & Ezugwu, A. E. Automatic detection and classification of lung cancer CT scans based on deep learning and Ebola optimization search algorithm. PLoS ONE 18(8), e0285796 (2023).","journal-title":"PLoS ONE"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-31432-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-31432-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-31432-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T12:58:19Z","timestamp":1768395499000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-31432-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,24]]},"references-count":31,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["31432"],"URL":"https:\/\/doi.org\/10.1038\/s41598-025-31432-0","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,24]]},"assertion":[{"value":"18 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1777"}}