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For this purpose, a large number of experimental works have been consulted, and a database with more than 1200 bioprinting tests has been created. These tests cover different combinations of conditions in terms of print pressure, temperature, and needle values, for example. These data are difficult to deal with in terms of determining combinations of conditions to optimize the tests and analyze new options. The best model demonstrated a specificity (Sp) of 88.4% and a sensitivity (Sn) of 86.2% in the training series while achieving an Sp of 85.9% and an Sn of 80.3% in the external validation series. This model utilizes operators based on perturbation theory to analyze the complexity of the data. For comparative purposes, neural networks have been used, and very similar results have been obtained. The developed tool could easily be applied to predict the properties of bioprinting assays in silico. These findings could significantly improve the efficiency and accuracy of predictive models in bioprinting without resorting to trial-and-error tests, thereby saving time and funds. Ultimately, this tool may help pave the way for advances in personalized medicine and tissue engineering.<\/jats:p>","DOI":"10.3390\/polym17010121","type":"journal-article","created":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T04:37:10Z","timestamp":1736138230000},"page":"121","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Artificial Intelligence-Driven Modeling for Hydrogel Three-Dimensional Printing: Computational and Experimental Cases of Study"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9055-0721","authenticated-orcid":false,"given":"Harbil","family":"Bediaga-Ba\u00f1eres","sequence":"first","affiliation":[{"name":"Department of Physical Chemistry, University of Basque Country UPV\/EHU, 48940 Leioa, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8714-9120","authenticated-orcid":false,"given":"Isabel","family":"Moreno-Ben\u00edtez","sequence":"additional","affiliation":[{"name":"Department of Organic and Inorganic Chemistry, University of Basque Country UPV\/EHU, 48940 Leioa, Spain"}]},{"given":"Sonia","family":"Arrasate","sequence":"additional","affiliation":[{"name":"Department of Organic and Inorganic Chemistry, University of Basque Country UPV\/EHU, 48940 Leioa, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0543-4134","authenticated-orcid":false,"given":"Leyre","family":"P\u00e9rez-\u00c1lvarez","sequence":"additional","affiliation":[{"name":"Department of Physical Chemistry, University of Basque Country UPV\/EHU, 48940 Leioa, Spain"},{"name":"BCMaterials, Basque Center for Materials, Applications and Nanostructures, UPV\/EHU Science Park, 48940 Leioa, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4818-9047","authenticated-orcid":false,"given":"Amit K.","family":"Halder","sequence":"additional","affiliation":[{"name":"LAQV-REQUIMTE, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal"},{"name":"Dr. B. 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