VGG-16, VGG-16 With Random Forest, Resnet50 With SVM, and EfficientNetB0 With XGBoost-Enhancing Bone Fracture Classification in X-Ray Using Deep Learning Models

VGG-16, VGG-16 With Random Forest, Resnet50 With SVM, and EfficientNetB0 With XGBoost-Enhancing Bone Fracture Classification in X-Ray Using Deep Learning Models

Millions of cases of bone fractures are reported every year, and accuracy in classification is crucial to help with proper management and treatment. The recently developed techniques of Machine Learning, particularly Deep Learning, have been effective in increasing diagnosis precision and efficiency...

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Bibliographic Details
Main Authors: Spoorthy Torne, Dasharathraj K. Shetty, Krishnamoorthi Makkithaya, Prasiddh Hegde, Manu Sudhi, Phani Kumar Pullela, T Tamil Eniyan, Ritesh Kamath, Staissy Salu, Pranav Bhat, S. Girisha, P. S. Priya
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Bone fracture
ensemble learning models
fracture classification
machine learning
medical imaging diagnostics
random forest
Online Access:https://ieeexplore.ieee.org/document/10855403/
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