Predicting no-shows for dental appointments

Patient no-shows is a significant problem in healthcare, reaching up to 80% of booked appointments and costing billions of dollars. Predicting no-shows for individual patients empowers clinics to implement better mitigation strategies. Patients’ no-show behavior varies across health clinics and the...

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Detalles Bibliográficos
Autores principales: Alabdulkarim, Yazeed, Almukaynizi, Mohammed, Alameer, Abdulmajeed, Makanati, Bassil, Althumairy, Riyadh, Almaslukh, Abdulaziz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680883/
https://www.ncbi.nlm.nih.gov/pubmed/36426240
http://dx.doi.org/10.7717/peerj-cs.1147

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680883/
https://www.ncbi.nlm.nih.gov/pubmed/36426240
http://dx.doi.org/10.7717/peerj-cs.1147

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