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Notably, 15 of the deaths occurred among ICU patients, whereas only one death occurred outside the ICU. For each patient, 32 amino acid concentrations were used as input for machine-learning (ML) models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among the classification models evaluated for predicting ICU admission, XGBOOST and LASSO achieved the highest performance, each with an AUC of 0.958. Arginine and glutamic acid consistently emerged as the most predictive features across all models, followed by 1-methyl-L-histidine, tryptophan, and tyrosine, which appeared among the top variables in four of the five best-performing models. In survival analysis, the mean concordance index (and integrated Brier score) was 0.973 (0.10) for Survival LASSO, 0.971 (0.11) for RFSRC, and 0.942 (0.12) for Survival XGBOOST. In survival models, the top five amino acids contributing to predictions were ornithine, gamma-aminobutyric acid, ethanolamine, arginine, and histidine.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>ML models based on amino-acid profiles can accurately predict disease progression in CCHF, supporting early risk stratification and providing insights into the metabolic mechanisms underlying disease severity.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12879-026-13787-5","type":"journal-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T07:14:26Z","timestamp":1782803666000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine learning-based prediction of ICU admission and mortality in Crimean\u2013Congo hemorrhagic fever by using wide-range targeted metabolomics"],"prefix":"10.1186","volume":"26","author":[{"given":"Ahu","family":"Cephe","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyit Ali","family":"B\u00fcy\u00fcktuna","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Necla","family":"Ko\u00e7han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00f6zde Ert\u00fcrk","family":"Zarars\u0131z","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Serra \u0130layda","family":"Yerlita\u015f","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K\u00fcbra","family":"Do\u011fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Demet","family":"Kablan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00f6khan","family":"Ba\u011fc\u0131","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Selda","family":"\u00d6zer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cihad","family":"Baysal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasemin \u00c7ak\u0131r","family":"K\u0131ymaz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Halef Okan","family":"Do\u011fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00f6kmen","family":"Zarars\u0131z","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,30]]},"reference":[{"issue":"12","key":"13787_CR1","doi-asserted-by":"publisher","first-page":"e00749-24","DOI":"10.1128\/mra.00749-24","volume":"13","author":"G Boshevska","year":"2024","unstructured":"Boshevska G, Emmerich P, von Possel R, Jancheska E, Buzharova T, Kochinski D, et al. 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