Comparison of NQE combined with SVC, NN, and QCNN classifiers. The table shows the number of test cases, comparison with classical classifiers, and data imbalance issues in this and previous work.

Comparison of NQE combined with SVC, NN, and QCNN classifiers. The table shows the number of test cases, comparison with classical classifiers, and data imbalance issues in this and previous work.

<p>Comparison of NQE combined with SVC, NN, and QCNN classifiers. The table shows the number of test cases, comparison with classical classifiers, and data imbalance issues in this and previous work.</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Aninda Astuti (21736334) (author)
مؤلفون آخرون: Pin-Keng Shih (13200121) (author), Shan-Chih Lee (493837) (author), Venugopala Reddy Mekala (21736337) (author), Ezra B. Wijaya (21736340) (author), Ka-Lok Ng (9295900) (author)
منشور في: 2025
الموضوعات:
Medicine
Cell Biology
Cancer
Space Science
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
solving intricate problems
improved execution time
cancer cell dissemination
neural quantum embedding
combines quantum computing
qnn algorithms compared
despite extensive research
identifying metastasis biomarkers
complex metastasis process
qml &# 8217
binary classification problem
binary classification
hybrid quantum
research delves
classical algorithms
study addresses
stage approach
offering potential
machine learning
high lethality
drawing inspiration
daunting task
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