Story perspectives

Classical Machine Learning Outperforms Quantum in CKD Diagnosis

11/14/2025

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Summary

Story summary

Florida Atlantic University researchers compared classical and quantum machine learning methods for diagnosing chronic kidney disease (CKD).
Using Principal Component Analysis (PCA) and Singular Value Decomposition (SVD), the Classical SVM achieved 98.75% accuracy with PCA.
The Quantum SVM reached 87.5% accuracy.
The Classical SVM was up to 42 times faster than the Quantum SVM.
Future work will use larger datasets and optimize feature selection to enhance CKD diagnostics.

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Story summary

Florida Atlantic University researchers compared classical and quantum machine learning methods for diagnosing chronic kidney disease (CKD).
Using Principal Component Analysis (PCA) and Singular Value Decomposition (SVD), the Classical SVM achieved 98.75% accuracy with PCA.
The Quantum SVM reached 87.5% accuracy.
The Classical SVM was up to 42 times faster than the Quantum SVM.
Future work will use larger datasets and optimize feature selection to enhance CKD diagnostics.