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We aim to perform a scoping review to synthesize the literature in the last 10 years on integrating AI in the approach to this condition and highlight aspects of research into its prediction, diagnosis and treatment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A search was performed via PubMed, Science Direct, Scopus, and LILACS from 2014 to 2024, in which 649 articles were identified, and 3 studies were identified via the snowball method; the title and abstract were identified, and 35 articles were obtained for full reading. Finally, 25 studies were selected after applying the inclusion and exclusion criteria to execute this review.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The articles reviewed included different types of studies, with observational and experimental studies being frequent and systematic reviews and narratives being less frequent. Similarly, there was evidence of a generalized distribution, with a greater concentration in the United States. These studies were analyzed according to the use of AI applied to cleft lip\/palate, obtaining 6 subcategories, including diagnosis, prediction, treatment, and education, in which different types of AI models were included, most frequently using deep learning and machine learning.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These technologies promise to optimize the care of patients with this condition. Although current advances are promising, further research is essential to expand and refine their beneficial use. AI has driven significant advances in various stages of the cleft lip and\/or palate approach, integrating tools such as assisted algorithms, genetics-based predictive models, and advanced surgical planning.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s10006-025-01371-1","type":"journal-article","created":{"date-parts":[[2025,4,10]],"date-time":"2025-04-10T01:08:56Z","timestamp":1744247336000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Revolutionizing cleft lip and palate management through artificial intelligence: a scoping review"],"prefix":"10.1007","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-0383-6519","authenticated-orcid":false,"given":"Cristhian David Barreto","family":"Zambrano","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-5671-518X","authenticated-orcid":false,"given":"Mariana Arias","family":"Jim\u00e9nez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4090-2300","authenticated-orcid":false,"given":"Angela Gabriela Mu\u00f1oz","family":"Rodr\u00edguez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7189-5863","authenticated-orcid":false,"given":"Erwin Hernando Hern\u00e1ndez","family":"Rinc\u00f3n","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,4,10]]},"reference":[{"key":"1371_CR1","doi-asserted-by":"publisher","unstructured":"Castro P (2017) Computing machinery, intelligence and undecidability. 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