Quick Navigation
Topics
Quantum Machine Learning
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.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.