Real-time acoustic sensing and artificial intelligence for error prevention in orthopedic surgery
Abstract In this work, we developed and validated a computer method capable of robustly detecting drill breakthrough events and show the potential of deep learning-based acoustic sensing for surgical error prevention. Bone drilling is an essential part of orthopedic surgery and has a high risk of in...
Guardado en:
Autores principales: | Matthias Seibold, Steven Maurer, Armando Hoch, Patrick Zingg, Mazda Farshad, Nassir Navab, Philipp Fürnstahl |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/7b5291b82bb6434497d62afbc29738c1 |
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