{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T12:08:32Z","timestamp":1785154112581,"version":"3.55.0"},"reference-count":22,"publisher":"Walter de Gruyter GmbH","license":[{"start":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T00:00:00Z","timestamp":1785196800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Ethical Standards of Altinbas University Ethics Committee","award":["2022\/157"],"award-info":[{"award-number":["2022\/157"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"j_bmt-2024-0628_abs_001\">\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This study aimed to apply machine learning (ML) models to enhance lung cancer (LC) classification, distinguishing malignant from benign tumors, using data from 73 patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_bmt-2024-0628_abs_002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The dataset included PET\/CT biomarkers and demographic factors, with SMOTE applied to address class imbalance. Three models were evaluated using 10-fold cross-validation to compare Random Forest (RF), Decision Tree (DT), Extra Trees Classifier (ETC), and XGBoost algorithms based on accuracy and\u00a0AUC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_bmt-2024-0628_abs_003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>ETC performed best in Model 1 (86\u202f% accuracy, AUC 0.95), RF in Model 2 (94\u202f% accuracy, AUC 0.97), and XGBoost in Model 3 (94\u202f% accuracy, AUC 0.98). XGBoost consistently outperformed others, particularly in Model 3, which included age and smoking. Feature importance analysis highlighted SUVmax as the most predictive variable, with smoking having a moderate influence and gender being minimal.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_bmt-2024-0628_abs_004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Integrating clinical and lifestyle data with PET\/CT parameters significantly improved LC classification. XGBoost emerged as the most effective model, demonstrating that comprehensive models enhance diagnostic accuracy beyond traditional metrics.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1515\/bmt-2024-0628","type":"journal-article","created":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T11:57:41Z","timestamp":1785153461000},"source":"Crossref","is-referenced-by-count":0,"title":["Classification of malignant\/benign groups in lung cancer by machine learning and investigation of feature significance of parameters"],"prefix":"10.1515","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4778-1920","authenticated-orcid":false,"given":"Gonul","family":"Caliskan","sequence":"first","affiliation":[{"name":"Physiotherapy and Rehabilitation Master Program , Istanbul Bilgi University, Institute of Graduate Programs , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4579-5057","authenticated-orcid":false,"given":"Emre","family":"Alatas","sequence":"additional","affiliation":[{"name":"Faculty of Management Sciences, Department of Management Information Systems , Bogazici University , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0556-2808","authenticated-orcid":false,"given":"Sevilay","family":"Koksal","sequence":"additional","affiliation":[{"name":"Nuclear Physics Master Program , Istanbul University, Institute of Science and Technology , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4815-3674","authenticated-orcid":false,"given":"Safak","family":"Yigit","sequence":"additional","affiliation":[{"name":"Vocational School, Physiotherapy Program , Istanbul Galata University , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9373-8693","authenticated-orcid":false,"given":"Resit","family":"Akyel","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine , Yedikule Chest Diseases Hospital , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0089-0499","authenticated-orcid":false,"given":"Iffet","family":"Cavdar","sequence":"additional","affiliation":[{"name":"Faculty of Science, Department of Nuclear Physics , Istanbul University , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2268-9606","authenticated-orcid":false,"given":"Goksel","family":"Alcin","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine , Istanbul Training and Research Hospital , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9222-8883","authenticated-orcid":false,"given":"Esra","family":"Arslan","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine , Istanbul Training and Research Hospital , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6359-5908","authenticated-orcid":false,"given":"Tuba","family":"Ciftci-Kusbeci","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Department of Chest Diseases , Alt\u0131nba\u015f University , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1572-0620","authenticated-orcid":false,"given":"Elcin","family":"Dereli","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Physiotherapy and Rehabilitation Program , Istanbul Bilgi University , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5625-9749","authenticated-orcid":false,"given":"Elife","family":"Akgun","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine , Istanbul Training and Research Hospital , Istanbul , T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5231-2768","authenticated-orcid":false,"given":"Handan","family":"Tanyildizi-Kokkulunk","sequence":"additional","affiliation":[{"name":"Vocational School of Health Sciences, Radiotherapy Program , Alt\u0131nba\u015f University , Istanbul , T\u00fcrkiye"},{"name":"Department of Arts & Sciences , Maine Maritime Academy , Castine , ME , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2026,7,28]]},"reference":[{"key":"2026072711573789888_j_bmt-2024-0628_ref_001","doi-asserted-by":"crossref","unstructured":"Sung, H, Ferlay, J, Siegel, RL, Laversanne, M, Soerjomataram, I, Jemal, A, et al.. 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