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Cancer Detection Using Quantum Neural Networks: A Demonstration on a Quantum Computer

arXiv
Authors: Nilima Mishra, Aradh Bisarya, Shubham Kumar, Bikash K. Behera, Sabyasachi Mukhopadhyay, Prasanta K. Panigrahi

Year

2019

Paper ID

15109

Status

Preprint

Abstract Read

~2 min

Abstract Words

130

Citations

N/A

Abstract

Artificial intelligence and machine learning paves the way to achieve greater technical feats. In this endeavor to hone these techniques, quantum machine learning is budding to serve as an important tool. Using the techniques of deep learning and supervised learning in the quantum framework, we are able to propose a quantum neural network and showcase its implementation. We consider the application of cancer detection to demonstrate the working of our quantum neural network. Our focus is to train the network of ten qubits in a way so that it can learn the label of the given data set and optimize the circuit parameters to obtain the minimum error. Thus, through the use of many algorithms, we are able to give an idea of how a quantum neural network can function.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2019 reference point for readers tracking recent quantum research.
  • Artificial intelligence and machine learning paves the way to achieve greater technical feats.

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Current Paper #15109 #69034 Hardware-aware Low-latency Quan... #69025 Machine-Learning Optimization a... #69003 QBugLM: An Agentic Benchmarking... #68993 Tomography of quantum states wi...

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