A deep learning approach using an ensemble model to autocreate an image-based hip fracture registry

A deep learning approach using an ensemble model to autocreate an image-based hip fracture registry

Abstract. Objectives:. With more than 300,000 patients per year in the United States alone, hip fractures are one of the most common injuries occurring in the elderly. The incidence is predicted to rise to 6 million cases per annum worldwide by 2050. Many fracture registries have been established, s...

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Bibliographic Details
Main Authors: Jacobien H.F. Oosterhoff, MD, PhD, Soomin Jeon, PhD, Bardiya Akhbari, PhD, David Shin, BS, Daniel G. Tobert, MD, Synho Do, PhD, Soheil Ashkani-Esfahani, MD, Hamid Ghaednia, PhD, Joseph H. Schwab, MD, MS
Format: Article
Language:English
Published: Wolters Kluwer 2024-01-01
Series:OTA International
Online Access:http://journals.lww.com/10.1097/OI9.0000000000000283

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http://journals.lww.com/10.1097/OI9.0000000000000283

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