Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Prevalence of Machine Learning in Craniofacial Surgery
9
Zitationen
3
Autoren
2020
Jahr
Abstract
Machine learning (ML) revolves around the concept of using experience to teach computer-based programs to reliably perform specific tasks. Healthcare setting is an ideal environment for adaptation of ML applications given the multiple specific tasks that could be allocated to computer programs to perform. There have been several scoping reviews published in literature looking at the general acceptance and adaptability of surgical specialities to ML applications, but very few focusing on the application towards craniofacial surgery. This study aims to present a detailed scoping review regarding the use of ML applications in craniofacial surgery.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.439 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.315 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.756 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.526 Zit.