{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T17:53:21Z","timestamp":1791395601651,"version":"4.3.3"},"reference-count":64,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T00:00:00Z","timestamp":1739923200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Physiol."],"abstract":"<jats:sec><jats:title>Objectives<\/jats:title><jats:p>Lumbar spinal stenosis (LSS) is an increasingly important issue related to back pain in elderly patients, resulting in significant socioeconomic burdens. Postoperative complications and socioeconomic effects are evaluated using the clinical parameter of hospital length of stay (LOS). This study aimed to develop a machine learning-based tool that can calculate the risk of prolonged length of stay (PLOS) after surgery and interpret the results.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Patients were registered from the spine surgery department in our hospital. Hospital stays greater than or equal to the 75th percentile for LOS was considered extended PLOS after spine surgery. We screened the variables using the least absolute shrinkage and selection operator (LASSO) and permutation importance value and selected nine features. We then performed hyperparameter selection via grid search with nested cross-validation. Receiver operating characteristics curve, calibration curve and decision curve analysis was carried out to assess model performance. The result of the final selected model was interpreted using Shapley Additive exPlanations (SHAP), and Local Interpretable Model-agnostic Explanations (LIME) were used for model interpretation. To facilitate model utilization, a web application was deployed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 540 patients were involved, and several features were finally selected. The final optimal random forest (RF) model achieved an area under the curve (ROC) of 0.93 on the training set and 0.83 on the test set. Based on both SHAP and LIME analyses, intraoperative blood loss emerged as the most significant contributor to the outcome.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Machine learning in association with SHAP and LIME can provide a clear explanation of personalized risk prediction, and spine surgeons can gain a perceptual grasp of the impact of important model components. Utilization and future clinical research of our RF model are made simple and accessible through the web application.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fphys.2025.1542240","type":"journal-article","created":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T06:52:49Z","timestamp":1739947969000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Web-based machine learning application for interpretable prediction of prolonged length of stay after lumbar spinal stenosis surgery: a retrospective cohort study with explainable AI"],"prefix":"10.3389","volume":"16","author":[{"given":"Paierhati","family":"Yasheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alimujiang","family":"Yusufu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasenjiang","family":"Yimiti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haopeng","family":"Luan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cong","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinghua","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,2,19]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"4305","DOI":"10.1007\/s00464-019-07197-9","article-title":"Impact of laparoscopic approach on the short-term outcomes of elderly patients with colorectal cancer: a nationwide Italian experience","volume":"34","author":"Barina","year":"2020","journal-title":"Surg. Endosc."},{"key":"B2","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1097\/BRS.0000000000000276","article-title":"Patient characteristics associated with increased postoperative length of stay and readmission after elective laminectomy for lumbar spinal stenosis","volume":"39","author":"Basques","year":"2014","journal-title":"Spine (Phila Pa 1976)"},{"key":"B3","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/s13018-022-03464-z","article-title":"Predisposing factors for allogeneic blood transfusion in patients with ankylosing spondylitis undergoing primary unilateral total hip arthroplasty: a retrospective study","volume":"18","author":"Bian","year":"2023","journal-title":"J. Orthop. Surg. Res."},{"key":"B4","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1007\/s10115-012-0487-8","article-title":"A review of feature selection methods on synthetic data","volume":"34","author":"Bolon-Canedo","year":"2013","journal-title":"Knowl. Inf. Syst."},{"key":"B5","doi-asserted-by":"publisher","first-page":"1882","DOI":"10.1021\/ci0341161","article-title":"Comparison of support vector machine and artificial neural network systems for drug\/nondrug classification","volume":"43","author":"Byvatov","year":"2003","journal-title":"J. Chem. Inf. Comput. Sci."},{"key":"B6","doi-asserted-by":"publisher","first-page":"S2-S8","DOI":"10.1093\/pm\/pnz245","article-title":"Cost-effectiveness and safety of interspinous process decompression (superion)","volume":"20","author":"Cairns","year":"2019","journal-title":"Pain Med."},{"key":"B7","doi-asserted-by":"publisher","first-page":"2743","DOI":"10.3892\/etm.2020.9001","article-title":"Biportal endoscopic decompression vs. microscopic decompression for lumbar canal stenosis: a systematic review and meta-analysis","volume":"20","author":"Chen","year":"2020","journal-title":"Exp. Ther. Med."},{"key":"B8","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1080\/02688697.2016.1206188","article-title":"Transforaminal epidural steroid injection in lumbar spinal stenosis: an observational study with two-year follow-up","volume":"31","author":"Davis","year":"2017","journal-title":"Br. J. Neurosurg."},{"key":"B9","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1016\/j.wneu.2019.06.181","article-title":"Enhanced recovery after surgery (ERAS) for spine surgery: a systematic review","volume":"130","author":"Dietz","year":"2019","journal-title":"World Neurosurg."},{"key":"B10","doi-asserted-by":"publisher","first-page":"5261","DOI":"10.1007\/s10462-022-10304-3","article-title":"Explainable AI for clinical and remote health applications: a survey on tabular and time series data","volume":"56","author":"Di Martino","year":"2022","journal-title":"Artif. Intell. Rev."},{"key":"B11","doi-asserted-by":"publisher","first-page":"4385","DOI":"10.3390\/s20164385","article-title":"Interpretability of input representations for gait classification in patients after total hip arthroplasty","volume":"20","author":"Dindorf","year":"2020","journal-title":"Sensors (Basel)"},{"key":"B12","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1186\/1472-6947-12-136","article-title":"A multiscale and multiparametric approach for modeling the progression of oral cancer","volume":"12","author":"Exarchos","year":"2012","journal-title":"BMC Med. Inf. Decis. Mak."},{"key":"B13","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1007\/s00586-016-4668-0","article-title":"The clinical course of pain and disability following surgery for spinal stenosis: a systematic review and meta-analysis of cohort studies","volume":"26","author":"Fritsch","year":"2017","journal-title":"Eur. Spine J."},{"key":"B14","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1186\/s13244-022-01311-7","article-title":"Reproducibility of artificial intelligence models in computed tomography of the head: a quantitative analysis","volume":"13","author":"Gunzer","year":"2022","journal-title":"Insights Imaging"},{"key":"B15","article-title":"Real-time occupancy detection using decision trees with multiple sensor types","volume-title":"Proceedings of the 2011 symposium on simulation for architecture and urban design","author":"Hailemariam","year":"2011"},{"key":"B16","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1002\/per.2253","article-title":"Targeting item\u2013level nuances leads to small but robust improvements in personality prediction from digital footprints","volume":"34","author":"Hall","year":"2020","journal-title":"Eur. J. Personality"},{"key":"B17","doi-asserted-by":"publisher","first-page":"E1082-E1087","DOI":"10.1097\/BSD.0000000000000460","article-title":"A retrospective cohort study comparing the safety and efficacy of minimally invasive versus open surgical techniques in the treatment of spinal metastases","volume":"30","author":"Hikata","year":"2017","journal-title":"Clin. Spine Surg."},{"key":"B18","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1186\/s12874-020-01080-1","article-title":"Accuracy of random-forest-based imputation of missing data in the presence of non-normality, non-linearity, and interaction","volume":"20","author":"Hong","year":"2020","journal-title":"Bmc Med. Res. Methodol."},{"key":"B19","doi-asserted-by":"publisher","first-page":"770","DOI":"10.1001\/jamasurg.2018.1512","article-title":"Automated performance metrics and machine learning algorithms to measure surgeon performance and anticipate clinical outcomes in robotic surgery","volume":"153","author":"Hung","year":"2018","journal-title":"JAMA Surg."},{"key":"B20","doi-asserted-by":"publisher","first-page":"e765","DOI":"10.7717\/peerj-cs.765","article-title":"Frameworks for developing an agro-prosumer community group platform","volume":"7","author":"Jain","year":"2021","journal-title":"PeerJ Comput. Sci."},{"key":"B21","doi-asserted-by":"publisher","first-page":"1688","DOI":"10.1001\/jama.2022.5921","article-title":"Diagnosis and management of lumbar spinal stenosis: a review","volume":"327","author":"Katz","year":"2022","journal-title":"JAMA"},{"key":"B22","doi-asserted-by":"publisher","first-page":"120","DOI":"10.3346\/jkms.2016.31.1.120","article-title":"Factors affecting length of hospital stay and mortality in infected diabetic foot ulcers undergoing surgical drainage without major amputation","volume":"31","author":"Kim","year":"2016","journal-title":"J. Korean Med. Sci."},{"key":"B23","doi-asserted-by":"publisher","first-page":"3679","DOI":"10.1021\/acs.jcim.9b00457","article-title":"Target-specific prediction of ligand affinity with structure-based interaction fingerprints","volume":"59","author":"Leidner","year":"2019","journal-title":"J. Chem. Inf. Model"},{"key":"B24","doi-asserted-by":"publisher","first-page":"18","DOI":"10.3390\/e23010018","article-title":"Explainable AI: a review of machine learning interpretability methods","volume":"23","author":"Linardatos","year":"2020","journal-title":"Entropy (Basel)."},{"key":"B25","doi-asserted-by":"publisher","first-page":"347","DOI":"10.3390\/jpm12030347","article-title":"Enhanced recovery after surgery (ERAS) in DIEP-flap breast reconstructions-A comparison of two reconstructive centers with and without ERAS-protocol","volume":"12","author":"Linder","year":"2022","journal-title":"J. Pers. Med."},{"key":"B26","doi-asserted-by":"publisher","first-page":"925354","DOI":"10.3389\/fsurg.2022.925354","article-title":"Predicting prolonged postoperative length of stay risk in patients undergoing lumbar fusion surgery: development and assessment of a novel predictive nomogram","volume":"9","author":"Lu","year":"2022","journal-title":"Front. Surg."},{"key":"B27","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1038\/s42256-019-0138-9","article-title":"From local explanations to global understanding with explainable AI for trees","volume":"2","author":"Lundberg","year":"2020","journal-title":"Nat. Mach. Intell."},{"key":"B28","doi-asserted-by":"publisher","first-page":"1737","DOI":"10.1097\/BRS.0000000000002207","article-title":"Trends, complications, and costs for hospital admission and surgery for lumbar spinal stenosis","volume":"42","author":"Machado","year":"2017","journal-title":"Spine (Phila Pa 1976)"},{"key":"B29","doi-asserted-by":"publisher","first-page":"1906","DOI":"10.1177\/14759217211036880","article-title":"Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights","volume":"21","author":"Malekloo","year":"2022","journal-title":"Struct. Health Monit."},{"key":"B30","doi-asserted-by":"crossref","DOI":"10.1109\/ICST.2008.22","article-title":"State-based testing of Ajax web applications","volume-title":"2008 1st international conference on software testing, verification, and validation","author":"Marchetto","year":"2008"},{"key":"B31","doi-asserted-by":"publisher","first-page":"e0184198","DOI":"10.1371\/journal.pone.0184198","article-title":"Portfolio optimization for seed selection in diverse weather scenarios","volume":"12","author":"Marko","year":"2017","journal-title":"PLoS One"},{"key":"B32","doi-asserted-by":"publisher","first-page":"e1015","DOI":"10.7717\/peerj-cs.1015","article-title":"An enhanced Genetic Folding algorithm for prostate and breast cancer detection","volume":"8","author":"Mezher","year":"2022","journal-title":"PeerJ Comput. Sci."},{"key":"B33","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1186\/1756-0381-6-16","article-title":"LVQ-SMOTE - learning vector quantization based synthetic minority over-sampling technique for biomedical data","volume":"6","author":"Nakamura","year":"2013","journal-title":"BioData Min."},{"key":"B34","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1056\/NEJMp1606181","article-title":"Predicting the future - big data, machine learning, and clinical medicine","volume":"375","author":"Obermeyer","year":"2016","journal-title":"N. Engl. J. Med."},{"key":"B35","doi-asserted-by":"publisher","first-page":"2131","DOI":"10.1109\/TCBB.2019.2911071","article-title":"XGBoost model for chronic kidney disease diagnosis","volume":"17","author":"Ogunleye","year":"2019","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinforma."},{"key":"B36","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1186\/s13040-021-00243-0","article-title":"A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions","volume":"14","author":"Orlenko","year":"2021","journal-title":"BioData Min."},{"key":"B37","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1055\/s-0032-1307251","article-title":"Dispersal pattern of injectate after lumbar interlaminar epidural spinal injection evaluated with computerized tomography","volume":"2","author":"Paisley","year":"2012","journal-title":"Glob. Spine J."},{"key":"B38","doi-asserted-by":"publisher","first-page":"8315047","DOI":"10.1155\/2021\/8315047","article-title":"Metabolic syndrome prediction models using machine learning and sasang constitution type","volume":"2021","author":"Park","year":"2021","journal-title":"Evid. Based Complement. Altern. Med."},{"key":"B39","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1001\/jamasurg.2018.1153","article-title":"Performance of a genomic sequencing classifier for the preoperative diagnosis of cytologically indeterminate thyroid nodules","volume":"153","author":"Patel","year":"2018","journal-title":"JAMA Surg."},{"key":"B40","doi-asserted-by":"publisher","first-page":"3032","DOI":"10.3892\/etm.2019.7917","article-title":"Minimally invasive spine surgery decreases postoperative pain and inflammation for patients with lumbar spinal stenosis","volume":"18","author":"Peng","year":"2019","journal-title":"Exp. Ther. Med."},{"key":"B41","doi-asserted-by":"publisher","first-page":"31","DOI":"10.21037\/jss.2016.01.07","article-title":"Interspinous process spacers versus traditional decompression for lumbar spinal stenosis: systematic review and meta-analysis","volume":"2","author":"Phan","year":"2016","journal-title":"J. Spine Surg."},{"key":"B42","doi-asserted-by":"publisher","first-page":"1513","DOI":"10.1016\/j.spinee.2022.04.007","article-title":"Enhanced recovery after surgery (ERAS) improves return of physiological function in frail patients undergoing one-to two-level TLIFs: an observational retrospective cohort study","volume":"22","author":"Porche","year":"2022","journal-title":"Spine J."},{"key":"B43","doi-asserted-by":"publisher","first-page":"1347","DOI":"10.1056\/NEJMra1814259","article-title":"Machine learning in medicine","volume":"380","author":"Rajkomar","year":"2019","journal-title":"N. Engl. J. Med."},{"key":"B44","doi-asserted-by":"publisher","first-page":"S96","DOI":"10.1097\/01.brs.0000218250.51148.5b","article-title":"Use of minimally invasive surgical techniques in the management of thoracolumbar trauma: current concepts","volume":"31","author":"Rampersaud","year":"2006","journal-title":"Spine"},{"key":"B45","doi-asserted-by":"publisher","first-page":"148","DOI":"10.4103\/picr.PICR_87_17","article-title":"Common pitfalls in statistical analysis: logistic regression","volume":"8","author":"Ranganathan","year":"2017","journal-title":"Perspect. Clin. Res."},{"key":"B46","doi-asserted-by":"publisher","first-page":"2374289519873088","DOI":"10.1177\/2374289519873088","article-title":"Artificial intelligence and machine learning in pathology: the present landscape of supervised methods","volume":"6","author":"Rashidi","year":"2019","journal-title":"Acad. Pathol."},{"key":"B47","doi-asserted-by":"publisher","first-page":"784","DOI":"10.1177\/2192568218770769","article-title":"Degenerative lumbar spine disease: estimating global incidence and worldwide volume","volume":"8","author":"Ravindra","year":"2018","journal-title":"Glob. Spine J."},{"key":"B48","doi-asserted-by":"publisher","first-page":"105837","DOI":"10.1016\/j.asoc.2019.105837","article-title":"Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series","volume":"86","author":"Ribeiro","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"B49","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1213\/ANE.0b013e318230e9e0","article-title":"Review article: closed-loop systems in anesthesia: is there a potential for closed-loop fluid management and hemodynamic optimization?","volume":"114","author":"Rinehart","year":"2012","journal-title":"Anesth. Analg."},{"key":"B50","doi-asserted-by":"publisher","first-page":"E359-E363","DOI":"10.1097\/BSD.0000000000001006","article-title":"Intramuscular liposomal bupivacaine decreases length of stay and opioid usage following lumbar spinal fusion","volume":"33","author":"Roh","year":"2020","journal-title":"Clin. Spine Surg."},{"key":"B51","doi-asserted-by":"publisher","first-page":"4050","DOI":"10.3390\/jcm11144050","article-title":"Performance of artificial intelligence-based algorithms to predict prolonged length of stay after lumbar decompression surgery","volume":"11","author":"Saravi","year":"2022","journal-title":"J. Clin. Med."},{"key":"B52","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.neucom.2017.04.018","article-title":"An efficient instance selection algorithm for k nearest neighbor regression","volume":"251","author":"Song","year":"2017","journal-title":"Neurocomputing"},{"key":"B53","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1097\/BRS.0000000000000765","article-title":"Clinical outcome in lumbar decompression surgery for spinal canal stenosis in the aged population: a prospective Swiss multicenter cohort study","volume":"40","author":"Ulrich","year":"2015","journal-title":"Spine (Phila Pa 1976)"},{"key":"B54","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1186\/s12874-016-0254-8","article-title":"Least absolute shrinkage and selection operator type methods for the identification of serum biomarkers of overweight and obesity: simulation and application","volume":"16","author":"Vasquez","year":"2016","journal-title":"BMC Med. Res. Methodol."},{"key":"B55","first-page":"18","volume-title":"A low-effort analytics platform for visualizing evolving flask-based Python web services","author":"Vogel","year":"2017"},{"key":"B56","doi-asserted-by":"publisher","first-page":"104813","DOI":"10.1016\/j.compbiomed.2021.104813","article-title":"Interpretable prediction of 3-year all-cause mortality in patients with heart failure caused by coronary heart disease based on machine learning and SHAP","volume":"137","author":"Wang","year":"2021","journal-title":"Comput. Biol. Med."},{"key":"B57","doi-asserted-by":"publisher","first-page":"1364","DOI":"10.1213\/ANE.0000000000004727","article-title":"Perioperative anemia: prevention, diagnosis, and management throughout the spectrum of perioperative care","volume":"130","author":"Warner","year":"2020","journal-title":"Anesth. Analg."},{"key":"B58","doi-asserted-by":"publisher","first-page":"20408","DOI":"10.1038\/s41598-022-24784-4","article-title":"A cost-utility analysis between decompression only and fusion surgery for elderly patients with lumbar spinal stenosis and sagittal imbalance","volume":"12","author":"Won","year":"2022","journal-title":"Sci. Rep."},{"key":"B59","doi-asserted-by":"publisher","first-page":"2135","DOI":"10.3390\/ijms21062135","article-title":"Intervertebral disc diseases part 2: a review of the current diagnostic and treatment strategies for intervertebral disc disease","volume":"21","author":"Wu","year":"","journal-title":"Int. J. Mol. Sci."},{"key":"B60","doi-asserted-by":"publisher","first-page":"740","DOI":"10.21037\/atm-20-287","article-title":"Factors influencing the length of stay after mediastinal tumor resection in the setting of an enhanced recovery after surgery (ERAS)-TUBELESS protocol","volume":"8","author":"Wu","year":"","journal-title":"Ann. Transl. Med."},{"key":"B61","doi-asserted-by":"publisher","first-page":"527","DOI":"10.4097\/kjae.2012.63.6.527","article-title":"Risk score for postoperative complications in thoracic surgery","volume":"63","author":"Yang","year":"2012","journal-title":"Korean J. Anesthesiol."},{"key":"B62","doi-asserted-by":"publisher","first-page":"2298","DOI":"10.3390\/ma11112298","article-title":"Study on damage accumulation and life prediction with loads below fatigue limit based on a modified nonlinear model","volume":"11","author":"Zhang","year":"2018","journal-title":"Mater. (Basel)"},{"key":"B63","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1186\/s12937-015-0054-8","article-title":"Comparison of two nutrition assessment tools in surgical elderly inpatients in Northern China","volume":"14","author":"Zhou","year":"2015","journal-title":"Nutr. J."},{"key":"B64","doi-asserted-by":"publisher","first-page":"4641","DOI":"10.1109\/access.2018.2789428","article-title":"Class weights random forest algorithm for processing class imbalanced medical data","volume":"6","author":"Zhu","year":"2018","journal-title":"IEEE Access"}],"container-title":["Frontiers in Physiology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fphys.2025.1542240\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T06:52:53Z","timestamp":1739947973000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fphys.2025.1542240\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,19]]},"references-count":64,"alternative-id":["10.3389\/fphys.2025.1542240"],"URL":"https:\/\/doi.org\/10.3389\/fphys.2025.1542240","relation":{},"ISSN":["1664-042X"],"issn-type":[{"value":"1664-042X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,19]]},"article-number":"1542240"}}