Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Accuracy and reliability analysis of a machine learning based segmentation tool for intertrochanteric femoral fracture CT
14
Zitationen
7
Autoren
2022
Jahr
Abstract
The proposed AI segmentation tool could effectively segment the bony structures from IFF CTs with comparable performance of human experts. The 2D masks and 3D models generated from automatic segmentation were effective and reliable, which could benefit the injury detail evaluation and preoperative planning of IFFs.
Ähnliche Arbeiten
Guidance for conducting systematic scoping reviews
2015 · 7.161 Zit.
An estimate of the worldwide prevalence and disability associated with osteoporotic fractures
2006 · 4.596 Zit.
Clinician’s Guide to Prevention and Treatment of Osteoporosis
2014 · 4.024 Zit.
Incidence and Economic Burden of Osteoporosis-Related Fractures in the United States, 2005–2025
2006 · 3.996 Zit.
Guidelines for the Provision and Assessment of Nutrition Support Therapy in the Adult Critically Ill Patient
2016 · 3.847 Zit.
Autoren
Institutionen
- Shanghai First People's Hospital(CN)
- Shanghai East Hospital(CN)
- Sun Yat-sen University(CN)
- Third Affiliated Hospital of Sun Yat-sen University(CN)
- Union Hospital(CN)
- Shenzhen University Health Science Center(CN)
- Huazhong University of Science and Technology(CN)
- Beijing Academy of Artificial Intelligence(CN)
- Zhongshan Hospital(CN)
- Fudan University(CN)
- Tongji University(CN)
- Central Hospital of Putuo District(CN)