On six balanced subsets of a 309-patient lung cancer dataset, a quantum SVM with the PauliFeatureMap reached about 96% average accuracy, but all results are in-sample with no held-out test.
Application of support vector machine to diagnosis of lung cancer
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Investigating Quantum Feature Maps in Quantum Support Vector Machines for Lung Cancer Classification
On six balanced subsets of a 309-patient lung cancer dataset, a quantum SVM with the PauliFeatureMap reached about 96% average accuracy, but all results are in-sample with no held-out test.