A PCA-plus-4-qubit-amplitude-encoding feature fusion pipeline with an SVM classifier reaches 99% accuracy on a public multi-region bone X-ray dataset, matching a transfer-learning baseline while cutting reported feature extraction time by 82%.
Artificial intelligence -based applications for bone fracture detection using medical images: A systematic review,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
eess.IV 1years
2025 1verdicts
REJECT 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
A Hybrid Quantum Classical Pipeline for X Ray Based Fracture Diagnosis
A PCA-plus-4-qubit-amplitude-encoding feature fusion pipeline with an SVM classifier reaches 99% accuracy on a public multi-region bone X-ray dataset, matching a transfer-learning baseline while cutting reported feature extraction time by 82%.