{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:37:40Z","timestamp":1760060260425,"version":"build-2065373602"},"reference-count":58,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T00:00:00Z","timestamp":1755475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Gerencia Regional de Salud, Castilla y Le\u00f3n, Spain","award":["GRS 2255\/A\/20","GRS COVID91\/A\/20"],"award-info":[{"award-number":["GRS 2255\/A\/20","GRS COVID91\/A\/20"]}]},{"name":"Institute of Technology (University of Castilla-La Mancha)","award":["GRS 2255\/A\/20","GRS COVID91\/A\/20"],"award-info":[{"award-number":["GRS 2255\/A\/20","GRS COVID91\/A\/20"]}]},{"name":"Chair of Artificial Intelligence","award":["GRS 2255\/A\/20","GRS COVID91\/A\/20"],"award-info":[{"award-number":["GRS 2255\/A\/20","GRS COVID91\/A\/20"]}]},{"name":"Castilla-La Mancha Institute of Health Research","award":["GRS 2255\/A\/20","GRS COVID91\/A\/20"],"award-info":[{"award-number":["GRS 2255\/A\/20","GRS COVID91\/A\/20"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>The genetic background influences the outcomes of COVID-19. This study aimed to evaluate the incidence of polymorphisms in genes linked to the RAAS system, cytokine production, and vitamin D on COVID-19 severity, with the goal of gaining a deeper understanding of the genetic etiology related to COVID-19. This study involved 338 COVID-19 patients and employed machine learning methods to identify the genetic variants that most significantly affect COVID-19 severity. The results revealed that polymorphisms in the IL6, IL6R, IL1\u03b1, IL1R, IFN\u03b3, TNF\u03b1, CRP, VDR, VDBP, and ACE2 genes are the most significant genetic factors influencing COVID-19 prognosis, particularly in terms of the risks of COVID-19 pneumonia, mortality, rehospitalization, and associated mortality. The machine learning methods achieved an AUC of 0.86 for predicting COVID-19 pneumonia, mortality, and mortality related to rehospitalization, as well as an AUC of 0.85 for rehospitalization within the first year. These results confirm the crucial role of genetic background in COVID-19 prognosis, facilitating the identification of patients at increased risk. In summary, this research demonstrates that genetics-driven machine learning models can pinpoint patients at heightened risk by primarily focusing on genetic variants associated with ACE2, inflammation, and vitamin D.<\/jats:p>","DOI":"10.3390\/ijms26167975","type":"journal-article","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T16:22:33Z","timestamp":1755534153000},"page":"7975","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Machine Learning Approach to Understanding the Genetic Role in COVID-19 Prognosis: The Influence of Gene Polymorphisms Related to Inflammation, Vitamin D, and ACE2"],"prefix":"10.3390","volume":"26","author":[{"given":"Sof\u00eda","family":"Jaurrieta-Largo","sequence":"first","affiliation":[{"name":"Department of Pneumonology, University Clinical Hospital of Valladolid, 47003 Valladolid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2247-9679","authenticated-orcid":false,"given":"Jos\u00e9 Pablo","family":"Miramontes-Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, R\u00edo Hortega University Hospital, 47012 Valladolid, Spain"},{"name":"Department of Medicine, Faculty of Medicine, University of Valladolid, 47003 Valladolid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luis","family":"Corral-Gudino","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, R\u00edo Hortega University Hospital, 47012 Valladolid, Spain"},{"name":"Department of Medicine, Faculty of Medicine, University of Valladolid, 47003 Valladolid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miriam","family":"Gabella-Mart\u00edn","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, R\u00edo Hortega University Hospital, 47012 Valladolid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sof\u00eda","family":"P\u00e9rez-Arroyo","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, R\u00edo Hortega University Hospital, 47012 Valladolid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4603-9034","authenticated-orcid":false,"given":"Ana M.","family":"Torres","sequence":"additional","affiliation":[{"name":"Medical Analysis Expert Group, Castilla-La Mancha Institute of Health Research (IDISCAM), 45071 Toledo, Spain"},{"name":"Medical Analysis Expert Group, Institute of Technology, University of Castilla-La Mancha, 16071 Cuenca, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jorge","family":"Mateo","sequence":"additional","affiliation":[{"name":"Medical Analysis Expert Group, Castilla-La Mancha Institute of Health Research (IDISCAM), 45071 Toledo, Spain"},{"name":"Medical Analysis Expert Group, Institute of Technology, University of Castilla-La Mancha, 16071 Cuenca, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1723-217X","authenticated-orcid":false,"given":"Jos\u00e9 Luis","family":"P\u00e9rez-Castrill\u00f3n","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, R\u00edo Hortega University Hospital, 47012 Valladolid, Spain"},{"name":"Department of Medicine, Faculty of Medicine, University of Valladolid, 47003 Valladolid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7699-4388","authenticated-orcid":false,"given":"Ricardo","family":"Usategui-Mart\u00edn","sequence":"additional","affiliation":[{"name":"Department of Cell Biology, Faculty of Medicine, University of Valladolid, 47005 Valladolid, Spain"},{"name":"Unit of Excellence IOBA, University of Valladolid, 47005 Valladolid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1708","DOI":"10.1056\/NEJMoa2002032","article-title":"Clinical Characteristics of Coronavirus Disease 2019 in China","volume":"382","author":"Guan","year":"2020","journal-title":"N. Engl. J. Med."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Gong, Z., Song, T., Hu, M., Che, Q., Guo, J., Zhang, H., Li, H., Wang, Y., Liu, B., and Shi, N. (2024). Natural and socio-environmental factors in the transmission of COVID-19: A comprehensive analysis of epidemiology and mechanisms. BMC Public Health, 24.","DOI":"10.1186\/s12889-024-19749-3"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2000912","DOI":"10.1183\/13993003.00912-2020","article-title":"Understanding the renin-angiotensin-aldosterone-SARS-CoV axis: A comprehensive review","volume":"56","author":"Ingraham","year":"2020","journal-title":"Eur. Respir. J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1444","DOI":"10.1126\/science.abb2762","article-title":"Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2","volume":"367","author":"Yan","year":"2020","journal-title":"Science"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1038\/s41586-020-2179-y","article-title":"Structural basis of receptor recognition by SARS-CoV-2","volume":"581","author":"Shang","year":"2020","journal-title":"Nature"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1038\/nature03712","article-title":"Angiotensin-converting enzyme 2 protects from severe acute lung failure","volume":"436","author":"Imai","year":"2005","journal-title":"Nature"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1007\/s00134-019-05600-6","article-title":"Angiotensin-converting enzymes in acute respiratory distress syndrome","volume":"45","author":"Annoni","year":"2019","journal-title":"Intensive Care Med."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"875","DOI":"10.1038\/nm1267","article-title":"A crucial role of angiotensin converting enzyme 2 (ACE2) in SARS coronavirus\u2013induced lung injury","volume":"11","author":"Kuba","year":"2005","journal-title":"Nat. Med."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.1016\/S0140-6736(20)30628-0","article-title":"COVID-19: Consider cytokine storm syndromes and immunosuppression","volume":"395","author":"Mehta","year":"2020","journal-title":"Lancet"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"e46","DOI":"10.1016\/S2213-2600(20)30216-2","article-title":"COVID-19 cytokine storm: The interplay between inflammation and coagulation","volume":"8","author":"Jose","year":"2020","journal-title":"Lancet Respir. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.ajpath.2020.08.009","article-title":"Immunopathology of Hyperinflammation in COVID-19","volume":"191","author":"Gustine","year":"2021","journal-title":"Am. J. Pathol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Tan, L.Y., Komarasamy, T.V., and Balasubramaniam, V.R. (2021). Hyperinflammatory Immune Response and COVID-19: A Double Edged Sword. Front. Immunol., 12, Available online: https:\/\/www.frontiersin.org\/journals\/immunology\/articles\/10.3389\/fimmu.2021.742941\/full.","DOI":"10.3389\/fimmu.2021.742941"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41577-021-00663-3","article-title":"Vitamin D shuts down T cell-mediated inflammation","volume":"22","author":"Minton","year":"2022","journal-title":"Nat. Rev. Immunol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.jaut.2017.07.007","article-title":"Modulation of inflammatory and immune responses by vitamin D","volume":"85","author":"Colotta","year":"2017","journal-title":"J. Autoimmun."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"e1909","DOI":"10.1002\/rmv.1909","article-title":"Vitamin D modulation of innate immune responses to respiratory viral infections","volume":"27","author":"Zdrenghea","year":"2017","journal-title":"Rev. Med. Virol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Mohan, M., Cherian, J.J., and Sharma, A. (2020). Exploring links between vitamin D deficiency and COVID-19. PLoS Pathog., 16.","DOI":"10.1371\/journal.ppat.1008874"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"e107","DOI":"10.7861\/clinmed.2020-0301","article-title":"Does vitamin D deficiency increase the severity of COVID-19?","volume":"20","author":"Weir","year":"2020","journal-title":"Clin. Med."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Radujkovic, A., Hippchen, T., Tiwari-Heckler, S., Dreher, S., Boxberger, M., and Merle, U. (2020). Vitamin D Deficiency and Outcome of COVID-19 Patients. Nutrients, 12.","DOI":"10.3390\/nu12092757"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1016\/j.jinf.2020.03.041","article-title":"Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: A systematic review and meta-analysis","volume":"80","author":"Fu","year":"2020","journal-title":"J. Infect."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"e29404","DOI":"10.1002\/jmv.29404","article-title":"Genetic characteristics involved in COVID-19 severity. The CARGENCORS case-control study and meta-analysis","volume":"96","author":"Degano","year":"2024","journal-title":"J. Med. Virol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Velavan, T.P., Pallerla, S.R., R\u00fcter, J., Augustin, Y., Kremsner, P.G., Krishna, S., and Meyer, C.G. (2021). Host genetic factors determining COVID-19 susceptibility and severity. eBioMedicine, 72, Available online: https:\/\/www.thelancet.com\/journals\/ebiom\/article\/PIIS2352-3964(21)00422-9\/fulltext.","DOI":"10.1016\/j.ebiom.2021.103629"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/s41576-022-00478-5","article-title":"The human genetic epidemiology of COVID-19","volume":"23","author":"Niemi","year":"2022","journal-title":"Nat. Rev. Genet."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"101822","DOI":"10.1016\/j.artmed.2020.101822","article-title":"Automated machine learning: Review of the state-of-the-art and opportunities for healthcare","volume":"104","author":"Waring","year":"2020","journal-title":"Artif. Intell. Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1111\/joim.12822","article-title":"eDoctor: Machine learning and the future of medicine","volume":"284","author":"Handelman","year":"2018","journal-title":"J. Intern. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1007\/s42979-021-00592-x","article-title":"Machine Learning: Algorithms, Real-World Applications and Research Directions","volume":"2","author":"Sarker","year":"2021","journal-title":"SN Comput. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"e3310","DOI":"10.1002\/jgm.3310","article-title":"The impact of certain genetic variants (single nucleotide polymorphisms) on incidence and severity of COVID-19","volume":"23","author":"Abobaker","year":"2021","journal-title":"J. Gene Med."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e23662","DOI":"10.1016\/j.heliyon.2023.e23662","article-title":"Association of genetic polymorphisms with COVID-19 infection and outcomes: An updated meta-analysis based on 62 studies","volume":"10","author":"Ren","year":"2024","journal-title":"Heliyon"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"145102","DOI":"10.1016\/j.gene.2020.145102","article-title":"Angiotensin-converting enzymes (ACE, ACE2) gene variants and COVID-19 outcome","volume":"762","author":"Albaiceta","year":"2020","journal-title":"Gene"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"e2323","DOI":"10.1002\/rmv.2323","article-title":"Genetic polymorphisms of ACE1, ACE2, and TMPRSS2 associated with COVID-19 severity: A systematic review with meta-analysis","volume":"32","author":"Saengsiwaritt","year":"2022","journal-title":"Rev. Med. Virol."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Sabater Molina, M., Nicol\u00e1s Rocamora, E., Bendicho, A.I., V\u00e1zquez, E.G., Zorio, E., Rodriguez, F.D., Gil Ortu\u00f1o, C., Rodr\u00edguez, A.I., S\u00e1nchez-L\u00f3pez, A.J., and Jara Rubio, R. (2022). Polymorphisms in ACE, ACE2, AGTR1 genes and severity of COVID-19 disease. PLoS ONE, 17.","DOI":"10.1371\/journal.pone.0263140"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1122","DOI":"10.1126\/science.abm8108","article-title":"The immunology and immunopathology of COVID-19","volume":"375","author":"Merad","year":"2022","journal-title":"Science"},{"key":"ref_32","first-page":"1824","article-title":"Pharmacologic Treatments for Coronavirus Disease 2019 (COVID-19): A Review","volume":"323","author":"Sanders","year":"2020","journal-title":"JAMA"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"e2234","DOI":"10.1002\/rmv.2234","article-title":"Interindividual immunogenic variants: Susceptibility to coronavirus, respiratory syncytial virus and influenza virus","volume":"31","author":"Darbeheshti","year":"2021","journal-title":"Rev. Med. Virol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1186\/s12985-024-02597-3","article-title":"The role of inflammatory gene polymorphisms in severe COVID-19: A review","volume":"21","author":"Yip","year":"2024","journal-title":"Virol. J."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Vogi, V., Haschka, D., Forer, L., Schwendinger, S., Petzer, V., Coassin, S., Tancevski, I., Sonnweber, T., L\u00f6ffler-Ragg, J., and Puchhammer-St\u00f6ckl, E. (2025). Severe COVID-19 disease is associated with genetic factors affecting plasma ACE2 receptor and CRP concentrations. Sci. Rep., 15.","DOI":"10.1038\/s41598-025-89306-4"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1002\/jbmr.551","article-title":"Oral supplementation with 25(OH)D3 versus vitamin D3: Effects on 25(OH)D levels, lower extremity function, blood pressure, and markers of innate immunity","volume":"27","author":"Sidelnikov","year":"2012","journal-title":"J. Bone Miner. Res."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Malmberg, H.-R., Hanel, A., Taipale, M., Heikkinen, S., and Carlberg, C. (2021). Vitamin D Treatment Sequence Is Critical for Transcriptome Modulation of Immune Challenged Primary Human Cells. Front. Immunol., 12.","DOI":"10.3389\/fimmu.2021.754056"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1985","DOI":"10.1002\/jbmr.3884","article-title":"Vitamin D Metabolism Revised: Fall of Dogmas","volume":"34","author":"Bouillon","year":"2019","journal-title":"J. Bone Miner. Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.ajhg.2017.06.014","article-title":"Low-Frequency Synonymous Coding Variation in CYP2R1 Has Large Effects on Vitamin D Levels and Risk of Multiple Sclerosis","volume":"101","author":"Manousaki","year":"2017","journal-title":"Am. J. Hum. Genet."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10528-020-10010-1","article-title":"Vitamin D and Genetic Susceptibility to Multiple Sclerosis","volume":"59","author":"Scazzone","year":"2021","journal-title":"Biochem. Genet."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.bone.2015.06.018","article-title":"Calcium and bone homeostasis in heterozygous carriers of CYP24A1 mutations: A cross-sectional study","volume":"81","author":"Cools","year":"2015","journal-title":"Bone"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Kuan, V., Martineau, A.R., Griffiths, C.J., Hypp\u00f6nen, E., and Walton, R. (2013). DHCR7 mutations linked to higher vitamin D status allowed early human migration to Northern latitudes. BMC Evol. Biol., 13.","DOI":"10.1186\/1471-2148-13-144"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.gene.2015.02.024","article-title":"Regulation of the vitamin D receptor gene by environment, genetics and epigenetics","volume":"561","author":"Saccone","year":"2015","journal-title":"Gene"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Karc\u0131o\u011flu Batur, L., Dokur, M., Ko\u00e7, S., Karabay, M., Akcay, Z.N., Gunger, E., and Hekim, N. (2024). Investigation of the Relationship between Vitamin D Deficiency and Vitamin D-Binding Protein Polymorphisms in Severe COVID-19 Patients. Diagnostics, 14.","DOI":"10.3390\/diagnostics14171941"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"4419","DOI":"10.2147\/JIR.S470097","article-title":"Vitamin D Binding Protein: A Potential Factor in Geriatric COVID-19 Acute Lung Injury","volume":"17","author":"Jiang","year":"2024","journal-title":"J. Inflamm. Res."},{"key":"ref_46","first-page":"818","article-title":"The association of ACE1, ACE2, TMPRSS2, IFITM3 and VDR polymorphisms with COVID-19 severity: A systematic review and meta-analysis","volume":"21","author":"Dobrijevic","year":"2022","journal-title":"EXCLI J."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Tentolouris, N., Achilla, C., Anastasiou, I.A., Eleftheriadou, I., Tentolouris, A., Basoulis, D., Kosta, O., Lambropoulos, A., Yavropoulou, M.P., and Chatzikyriakidou, A. (2024). The Association of Vitamin D Receptor Polymorphisms with COVID-19 Severity. Nutrients, 16.","DOI":"10.3390\/nu16050727"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1097\/RTI.0000000000000541","article-title":"Review of Chest Radiograph Findings of COVID-19 Pneumonia and Suggested Reporting Language","volume":"35","author":"Litmanovich","year":"2020","journal-title":"J. Thorac. Imaging"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/978-1-61737-954-3_6","article-title":"Targeted SNP genotyping using the TaqMan\u00ae assay","volume":"Volume 700","author":"Schleinitz","year":"2011","journal-title":"Disease Gene Identification: Methods and Protocols"},{"key":"ref_50","first-page":"1","article-title":"Xgboost: Extreme gradient boosting","volume":"1","author":"Chen","year":"2015","journal-title":"Sci. Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.neucom.2019.10.118","article-title":"A comprehensive survey on support vector machine classification: Applications, challenges and trends","volume":"408","author":"Cervantes","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"20","DOI":"10.38094\/jastt20165","article-title":"Classification Based on Decision Tree Algorithm for Machine Learning","volume":"2","author":"Charbuty","year":"2021","journal-title":"J. Appl. Sci. Technol. Trends"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3407","DOI":"10.31449\/inf.v45i2.3407","article-title":"Stock Market Prediction with Gaussian Na\u00efve Bayes Machine Learning Algorithm","volume":"45","author":"Ampomah","year":"2021","journal-title":"Informatica"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"117298","DOI":"10.1016\/j.eswa.2022.117298","article-title":"A bi-objective k-nearest-neighbors-based imputation method for multilevel data","volume":"204","author":"Cubillos","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"ref_55","unstructured":"(2025, April 23). MATLAB Runtime\u2014MATLAB Compiler. Available online: https:\/\/es.mathworks.com\/products\/compiler\/matlab-runtime.html."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Hutter, F., Kotthoff, L., and Vanschoren, J. (2019). Hyperparameter Optimization. Automated Machine Learning: Methods, Systems, Challenges, Springer International Publishing.","DOI":"10.1007\/978-3-030-05318-5"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1186\/s40537-020-00327-4","article-title":"Selecting critical features for data classification based on machine learning methods","volume":"7","author":"Chen","year":"2020","journal-title":"J. Big Data"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1186\/2196-1115-1-2","article-title":"A review of data mining using big data in health informatics","volume":"1","author":"Herland","year":"2014","journal-title":"J. Big Data"}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/16\/7975\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:30:22Z","timestamp":1760034622000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/26\/16\/7975"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,18]]},"references-count":58,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["ijms26167975"],"URL":"https:\/\/doi.org\/10.3390\/ijms26167975","relation":{},"ISSN":["1422-0067"],"issn-type":[{"type":"electronic","value":"1422-0067"}],"subject":[],"published":{"date-parts":[[2025,8,18]]}}}