{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T22:13:38Z","timestamp":1793830418024,"version":"4.6.1"},"reference-count":54,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005851","name":"Shahid Beheshti University of Medical Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005851","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Toxicology"],"published-print":{"date-parts":[[2024,5]]},"DOI":"10.1016\/j.tox.2024.153770","type":"journal-article","created":{"date-parts":[[2024,3,6]],"date-time":"2024-03-06T11:29:21Z","timestamp":1709724561000},"page":"153770","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":17,"special_numbering":"C","title":["Prediction of acute methanol poisoning prognosis using machine learning techniques"],"prefix":"10.1016","volume":"504","author":[{"given":"Mitra","family":"Rahimi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sayed Masoud","family":"Hosseini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Ali","family":"Mohtarami","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Babak","family":"Mostafazadeh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peyman Erfan Talab","family":"Evini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mobin","family":"Fathy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arya","family":"Kazemi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sina","family":"Khani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Mohammad","family":"Mortazavi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amirali","family":"Soheili","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Mohammad","family":"Vahabi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9401-0781","authenticated-orcid":false,"given":"Shahin","family":"Shadnia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.tox.2024.153770_bib1","unstructured":"Abdel Aziz, I., 1999. Effect of methyl alcohol administration on haematology and blood biochemistry of rabbits\u200b\u200b\u200b\u200b\u200b\u200b. Bethlehem Universit J. 18, 55\u201369 ((p))."},{"issue":"3","key":"10.1016\/j.tox.2024.153770_bib2","doi-asserted-by":"crossref","first-page":"293","DOI":"10.30565\/medalanya.1184894","article-title":"Risk factors associated with mortality in patients with methanol poisoning: a retrospective study","volume":"6","author":"Aydin","year":"2022","journal-title":"Acta Med. Alanya"},{"issue":"3","key":"10.1016\/j.tox.2024.153770_bib3","doi-asserted-by":"crossref","first-page":"293","DOI":"10.30565\/medalanya.1184894","article-title":"Risk factors associated with mortality in patients with methanol poisoning: a retrospective study","volume":"6","author":"AYDIN","year":"2022","journal-title":"Acta Med. Alanya"},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib4","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-022-25492-9","article-title":"Acute and chronic blood serum proteome changes in patients with methanol poisoning","volume":"12","author":"Cejnar","year":"2022","journal-title":"Sci. Rep."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib5","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1186\/s12882-019-1404-0","article-title":"Acute kidney injury and the risk of mortality in patients with methanol intoxication","volume":"20","author":"Chang","year":"2019","journal-title":"BMC Nephrol."},{"issue":"10","key":"10.1016\/j.tox.2024.153770_bib6","doi-asserted-by":"crossref","first-page":"900","DOI":"10.3109\/15563650.2011.630320","article-title":"Methanol and ethylene glycol acute poisonings \u2013 predictors of mortality","volume":"49","author":"Coulter","year":"2011","journal-title":"Clin. Toxicol."},{"issue":"3","key":"10.1016\/j.tox.2024.153770_bib7","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1001\/jamaophthalmol.2013.1463","article-title":"Methanol poisoning: predictors of visual outcomes","volume":"131","author":"Desai","year":"2013","journal-title":"JAMA Ophthalmol."},{"issue":"2","key":"10.1016\/j.tox.2024.153770_bib8","first-page":"57","article-title":"Predictors of poor outcomes in acute methanol poisoning","volume":"22","author":"Elbastawesy","year":"2022","journal-title":"Egypt. J. Forensic Sci. Appl. Toxicol."},{"issue":"2","key":"10.1016\/j.tox.2024.153770_bib9","doi-asserted-by":"crossref","first-page":"100","DOI":"10.21608\/esctj.2023.255311.1046","article-title":"Mortality prediction in acute methanol intoxication: role of poison severity score and sequential organ failure assessment score","volume":"11","author":"Eweda","year":"2023","journal-title":"Egypt. Soc. Clin. Toxicol. J."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib10","first-page":"1","article-title":"Middle East countries\u2019 contribution to global engineering research: a bibliometric analysis","volume":"19","author":"Fazeli-Varzaneh","year":"2021","journal-title":"Int. J. Inf. Sci. Manag. (IJISM)"},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib11","article-title":"Comparing the clinical characteristics\u00a0laboratory findings, and outcomes between epidemic and episodic methanol poisoning referrals; a cross-sectional study","volume":"9","author":"Hadipourzadeh","year":"2021","journal-title":"Arch. Acad. Emerg. Med."},{"issue":"7","key":"10.1016\/j.tox.2024.153770_bib12","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1177\/0960327106080077","article-title":"Prognostic factors in methanol poisoning","volume":"26","author":"Hassanian-Moghaddam","year":"2007","journal-title":"Hum. Exp. Toxicol."},{"issue":"2","key":"10.1016\/j.tox.2024.153770_bib13","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1080\/07853890.2019.1596302","article-title":"Extensive phenotype data and machine learning in prediction of mortality in acute coronary syndrome \u2013 the MADDEC study","volume":"51","author":"Hernesniemi","year":"2019","journal-title":"Ann. Med."},{"key":"10.1016\/j.tox.2024.153770_bib14","doi-asserted-by":"crossref","DOI":"10.1016\/j.tox.2023.153431","article-title":"Prediction of acute organophosphate poisoning severity using machine learning techniques","volume":"486","author":"Hosseini","year":"2023","journal-title":"Toxicology"},{"key":"10.1016\/j.tox.2024.153770_bib15","unstructured":"INFOSAN Quarterly Summary, 2020 #2. 2020; Available from: \u3008https:\/\/www.who.int\/news\/item\/29-07-2020-infosan-quarterly-summary-2020-2\u3009."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib16","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.amjms.2020.08.014","article-title":"Inpatient burden and mortality of methanol intoxication in the United States","volume":"361","author":"Kaewput","year":"2021","journal-title":"Am. J. Med. Sci."},{"issue":"3","key":"10.1016\/j.tox.2024.153770_bib17","doi-asserted-by":"crossref","first-page":"753","DOI":"10.1007\/s00167-022-06896-6","article-title":"Machine learning and conventional statistics: making sense of the differences","volume":"30","author":"Ley","year":"2022","journal-title":"Knee Surg.\u00a0Sports Traumatol., Arthrosc."},{"issue":"3","key":"10.1016\/j.tox.2024.153770_bib18","first-page":"175","article-title":"Prognostic factors in patients with methanol poisoning","volume":"36","author":"Liu","year":"1998","journal-title":"J. Toxicol.: Clin. Toxicol."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib19","doi-asserted-by":"crossref","first-page":"9741","DOI":"10.1038\/s41598-022-14007-1","article-title":"A cross-sectional multicenter linkage study of hospital admissions and mortality due to methanol poisoning in Iranian adults during the COVID-19 pandemic","volume":"12","author":"Mahdavi","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.tox.2024.153770_bib20","doi-asserted-by":"crossref","unstructured":"Md Noor, J., et al., Methanol outbreak: a Malaysian tertiary hospital experience. International journal of emergency medicine, 2020. 13: p. 1-7.","DOI":"10.1186\/s12245-020-0264-5"},{"key":"10.1016\/j.tox.2024.153770_bib21","unstructured":"Mehrpour, O., et al.,\u00a0n.d. Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS). Drug and Chemical Toxicology: p. 1-8.."},{"issue":"20","key":"10.1016\/j.tox.2024.153770_bib22","doi-asserted-by":"crossref","first-page":"57801","DOI":"10.1007\/s11356-023-26605-1","article-title":"Utility of artificial intelligence to identify antihyperglycemic agents poisoning in the USA: introducing a practical web application using National Poison Data System (NPDS)","volume":"30","author":"Mehrpour","year":"2023","journal-title":"Environ. Sci. Pollut. Res."},{"issue":"6","key":"10.1016\/j.tox.2024.153770_bib23","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1080\/17425255.2023.2232724","article-title":"Deep learning neural network derivation and testing to distinguish acute poisonings","volume":"19","author":"Mehrpour","year":"2023","journal-title":"Expert Opin. Drug Metab. Toxicol."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib24","doi-asserted-by":"crossref","DOI":"10.4103\/jrms.jrms_602_22","article-title":"The value of machine learning for prognosis prediction of diphenhydramine exposure: national analysis of 50,000 patients in the United States","volume":"28","author":"Mehrpour","year":"2023","journal-title":"J. Res. Med. Sci."},{"issue":"4","key":"10.1016\/j.tox.2024.153770_bib25","doi-asserted-by":"crossref","first-page":"692","DOI":"10.1080\/01480545.2022.2083149","article-title":"Decision tree algorithm can determine the outcome of repeated supratherapeutic ingestion (RSTI) exposure to acetaminophen: review of 4500 national poison data system cases","volume":"46","author":"Mehrpour","year":"2023","journal-title":"Drug Chem. Toxicol."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12911-022-02095-y","article-title":"Comparison of decision tree with common machine learning models for prediction of biguanide and sulfonylurea poisoning in the United States: an analysis of the National Poison Data System","volume":"23","author":"Mehrpour","year":"2023","journal-title":"BMC Med. Inform. Decis. Mak."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib27","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1111\/bcpt.13674","article-title":"Decision tree outcome prediction of acute acetaminophen exposure in the United States: a study of 30,000 cases from the National Poison Data System","volume":"130","author":"Mehrpour","year":"2022","journal-title":"Basic Clin. Pharmacol. Toxicol."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12911-022-01903-9","article-title":"Which model is superior in predicting ICU survival: artificial intelligence versus conventional approaches","volume":"22","author":"Mirzakhani","year":"2022","journal-title":"BMC Med. Inform. Decis. Mak."},{"key":"10.1016\/j.tox.2024.153770_bib29","doi-asserted-by":"crossref","DOI":"10.1016\/j.amsu.2021.102445","article-title":"Methanol poisoning as a new world challenge: A review","volume":"66","author":"Nekoukar","year":"2021","journal-title":"Ann. Med. Surg."},{"key":"10.1016\/j.tox.2024.153770_bib30","doi-asserted-by":"crossref","unstructured":"Osterhoudt, K.C.., Chapter 134 - Toxic Alcohols, in Pediatric Emergency Medicine, J.M. Baren, et al., Editors. 2008, W.B. Saunders: Philadelphia. p. 947-949.","DOI":"10.1016\/B978-141600087-7.50137-9"},{"issue":"9","key":"10.1016\/j.tox.2024.153770_bib31","doi-asserted-by":"crossref","first-page":"823","DOI":"10.3109\/15563650.2012.728224","article-title":"Risk factors related to poor outcome after methanol poisoning and the relation between outcome and antidotes\u2013a multicenter study","volume":"50","author":"Paasma","year":"2012","journal-title":"Clin. Toxicol."},{"issue":"9","key":"10.1016\/j.tox.2024.153770_bib32","doi-asserted-by":"crossref","first-page":"823","DOI":"10.3109\/15563650.2012.728224","article-title":"Risk factors related to poor outcome after methanol poisoning and the relation between outcome and antidotes \u2013 a multicenter study","volume":"50","author":"Paasma","year":"2012","journal-title":"Clin. Toxicol."},{"issue":"4","key":"10.1016\/j.tox.2024.153770_bib33","doi-asserted-by":"crossref","DOI":"10.3802\/jgo.2019.30.e65","article-title":"Prediction of survival outcomes in patients with epithelial ovarian cancer using machine learning methods","volume":"30","author":"Paik","year":"2019","journal-title":"J. Gynecol. Oncol."},{"key":"10.1016\/j.tox.2024.153770_bib34","unstructured":"Rafiei Tabatabaei, N., et al., Evaluation of Prog-nostic Factors of Methanol Poisoning in Patients Referred to Shahid Rajaei Hospital in Karaj. International Journal of Medical Toxicology and Forensic Medicine, 2021. 11(3): p. 34568."},{"issue":"3","key":"10.1016\/j.tox.2024.153770_bib35","article-title":"Intravenous plus intravitreal erythropoietin for management of methanol toxicity optic neuropathy: a case report and brief review","volume":"11","author":"Rashidi Alavijeh","year":"2023","journal-title":"Clin. Case Rep."},{"key":"10.1016\/j.tox.2024.153770_bib36","unstructured":"RespiratoryRate n.d.-CDC. Available from: \u3008https:\/\/www.cdc.gov\/dengue\/training\/cme\/ccm\/page57286.html#:~:text=Respiratory%20Rate&text=Deep%20and%20labored%20breathing%20pattern,%2C%20slow%2C%20labored%20and%20gasping\u3009."},{"issue":"3","key":"10.1016\/j.tox.2024.153770_bib37","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1007\/s13181-011-0142-x","article-title":"Hyperglycemia is a strong prognostic factor of lethality in methanol poisoning","volume":"7","author":"Sanaei-Zadeh","year":"2011","journal-title":"J. Med Toxicol."},{"issue":"10","key":"10.1016\/j.tox.2024.153770_bib38","first-page":"865","article-title":"Role of clinical and paraclinical manifestations of methanol poisoning in outcome prediction","volume":"18","author":"Shadnia","year":"2013","journal-title":"J. Res. Med. Sci.\u00a0Off. J. Isfahan Univ. Med. Sci."},{"issue":"10","key":"10.1016\/j.tox.2024.153770_bib39","first-page":"865","article-title":"Role of clinical and paraclinical manifestations of methanol poisoning in outcome prediction","volume":"18","author":"Shadnia","year":"2013","journal-title":"J. Res Med Sci."},{"issue":"43","key":"10.1016\/j.tox.2024.153770_bib40","doi-asserted-by":"crossref","first-page":"60511","DOI":"10.1007\/s11356-021-14998-w","article-title":"Predictors of poor outcomes among patients of acute methanol intoxication with particular reference to Sequential Organ Failure Assessment (SOFA) score","volume":"28","author":"Sharif","year":"2021","journal-title":"Environ. Sci. Pollut. Res."},{"key":"10.1016\/j.tox.2024.153770_bib41","doi-asserted-by":"crossref","DOI":"10.3389\/fmed.2023.1098138","article-title":"Factors affecting the severity and prognosis of visual damage in inhalational methanol poisoning","volume":"10","author":"Shen","year":"2023","journal-title":"Front. Med."},{"key":"10.1016\/j.tox.2024.153770_bib42","doi-asserted-by":"crossref","first-page":"1098138","DOI":"10.3389\/fmed.2023.1098138","article-title":"Factors affecting the severity and prognosis of visual damage in inhalational methanol poisoning","volume":"10","author":"Shen","year":"2023","journal-title":"Front. Med."},{"key":"10.1016\/j.tox.2024.153770_bib43","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.ijmedinf.2017.12.009","article-title":"Prediction models to identify individuals at risk of metabolic syndrome who are unlikely to participate in a health intervention program","volume":"111","author":"Shimoda","year":"2018","journal-title":"Int. J. Med. Inform."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib44","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1002\/ehf2.13073","article-title":"Machine learning vs. conventional statistical models for predicting heart failure readmission and mortality","volume":"8","author":"Shin","year":"2021","journal-title":"ESC Heart Fail."},{"issue":"4","key":"10.1016\/j.tox.2024.153770_bib45","doi-asserted-by":"crossref","first-page":"1500","DOI":"10.1080\/01480545.2020.1845192","article-title":"The outbreak of methanol intoxication during COVID-19 pandemic: prevalence of brain lesions and its predisposing factors","volume":"45","author":"Simani","year":"2022","journal-title":"Drug Chem. Toxicol."},{"key":"10.1016\/j.tox.2024.153770_bib46","unstructured":"Sivilotti, M.L.A., n.d.\u00a0Methanoland ethylene glycol poisongin UpToDate."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib47","doi-asserted-by":"crossref","first-page":"11","DOI":"10.12775\/JEHS.2023.45.01.001","article-title":"Poisoning with methanol and other non-beverage alcohols-an analysis of the issue based on hospitalizations in department of toxicology","volume":"45","author":"Sosnowska","year":"2023","journal-title":"J. Educ., Health Sport"},{"key":"10.1016\/j.tox.2024.153770_bib48","doi-asserted-by":"crossref","first-page":"4671671","DOI":"10.1155\/2022\/4671671","article-title":"Clinical Characteristics of Methanol-Induced Optic Neuropathy: Correlation between Aetiology and Clinical Findings","volume":"2022","author":"Sun","year":"2022","journal-title":"J. Ophthalmol."},{"issue":"5","key":"10.1016\/j.tox.2024.153770_bib49","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1097\/00005792-198109000-00005","article-title":"Epidemic methanol poisoning: clinical and biochemical analysis of a recent episode","volume":"60","author":"SWARTZ","year":"1981","journal-title":"Medicine"},{"issue":"4","key":"10.1016\/j.tox.2024.153770_bib50","article-title":"Evaluation of Prognostic Factors of Methanol Poisoning in Patients Referred to Shahid Rajaei Hospital in Karaj","volume":"11","author":"Tabatabaiei","year":"2021","journal-title":"Int. J. Med. Toxicol. Forensic Med."},{"issue":"4","key":"10.1016\/j.tox.2024.153770_bib51","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1080\/10915810490506795","article-title":"Acute renal injury following methanol poisoning: analysis of a case series","volume":"23","author":"Verhelst","year":"2004","journal-title":"Int. J. Toxicol."},{"key":"10.1016\/j.tox.2024.153770_bib52","first-page":"1","article-title":"Prognostic factors of outcome in methanol poisoning;\u00a0an 8-year retrospective cross-sectional study","volume":"8","author":"Yousefinejad","year":"2020","journal-title":"Arch. Acad. Emerg. Med."},{"issue":"1","key":"10.1016\/j.tox.2024.153770_bib53","article-title":"Prognostic factors of outcome in methanol poisoning; an 8-year retrospective cross-sectional study","volume":"8","author":"Yousefinejad","year":"2020","journal-title":"Arch. Acad. Emerg. Med"},{"key":"10.1016\/j.tox.2024.153770_bib54","doi-asserted-by":"crossref","first-page":"1779","DOI":"10.2147\/JMDH.S410301","article-title":"Machine learning and AI in cancer prognosis, prediction, and treatment selection: a critical approach","volume":"16","author":"Zhang","year":"2023","journal-title":"J. Multidiscip. Health"}],"container-title":["Toxicology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0300483X24000519?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0300483X24000519?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T05:23:28Z","timestamp":1763789008000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0300483X24000519"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5]]},"references-count":54,"alternative-id":["S0300483X24000519"],"URL":"https:\/\/doi.org\/10.1016\/j.tox.2024.153770","relation":{},"ISSN":["0300-483X"],"issn-type":[{"value":"0300-483X","type":"print"}],"subject":[],"published":{"date-parts":[[2024,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Prediction of acute methanol poisoning prognosis using machine learning techniques","name":"articletitle","label":"Article Title"},{"value":"Toxicology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.tox.2024.153770","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"153770"}}