Leveraging variational quantum-classical algorithms for enhanced lung cancer prediction

HIGHLIGHTS

  • What: This work explores the potential of and variational algorithms (VQCA) to forecast using a structured dataset. The authors provide a complete examination of the data stressing the better performance of the VQCA model and its promise in correctly predicting This study showcases the potential of VQCA and in predicting and underscores the benefits of techniques in healthcare analytics. By benchmarking the performance of VQCA against classical NNs and quantum NNs, this work seeks to evaluate its predictive capability and explore its potential as a transformative tool for early lung cancer detection.
  • Who: Philip Adebayo . . .

     

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