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Hybrid quantum computing based early detection of skin cancer

Vijayasri Iyer, Bhargava Ganti, A Vyshnavi, P. K. Krishnan Namboori, Sriram Iyer

2020Journal of Interdisciplinary Mathematics30 citationsDOI

Abstract

Abstract As image processing techniques constantly grow in complexity & volume, meeting the required demand for data storage and computational power is a challenge. Using hybrid quantum-mechanical systems to encode and process image information could help overcome such challenges. We propose to implement a hybrid quantum mechanical system with 2 qubits operation for the purpose of classifying between cancerous and non-cancerous pigmented skin-lesions in the HAM10000 dataset. In view of the ever-increasing number of skin cancer deaths, such a system could have potential for the early diagnosis of the disease. Until fully scalable quantum hardware becomes available, the hybrid model could be a viable alternative to overcome the limitations of classical computing systems.

Topics & Concepts

ENCODEComputer scienceQuantumScalabilityQubitQuantum computerProcess (computing)Hybrid systemArtificial intelligenceComputer engineeringComputational scienceTheoretical computer scienceMachine learningPhysicsBiologyQuantum mechanicsBiochemistryDatabaseOperating systemGeneCell Image Analysis TechniquesNeural Networks and Reservoir ComputingQuantum Information and Cryptography
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