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Quantum Machine Learning for Biomedical Data Analysis
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Author(s): Dankan Gowda V. (Department of Electronics and Communication Engineering, BMS Institute of Technology and Management, India), Harshali Yogesh Patil (Mumbai Educational Trust Institute of Computer Science, Mumbai, India), Shafiqul Abidin (Aligarh Muslim University, India), Ribhu Abhusan Panda (GIET University, Gunupur, India)and Sampathirao Suneetha (Andhra University College of Engineering, Andhra University, Visakhapatnam, India)
Copyright: 2024
Pages: 26
Source title:
Quantum Innovations at the Nexus of Biomedical Intelligence
Source Author(s)/Editor(s): Vishal Dutt (AVN Innovations Pvt. Ltd., India), Abhishek Kumar (Department of CSE, UIE, Chandigarh University, Punjab, India), Sachin Ahuja (Chandigarh University, India), Anupam Baliyan (Geeta University, India)and Narayan Vyas (AVN Innovations Pvt. Ltd., India)
DOI: 10.4018/979-8-3693-1479-1.ch011
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Abstract
The emerging and novel field of utilizing quantum physics in the world of machine learning, with applications customized for biomedical data, is explored in detail in this chapter. The discussion begins with an introduction to quantum physics and machine learning, before going on to explain how the two fields can work together to revolutionize biomedical data processing. Quantum-enhanced algorithms and their ability to process massive and intricate biomedical datasets are discussed in depth. In applications such as protein folding prediction, genomic data processing, and real-time diagnostics, the inherent parallelism and superposition capabilities of quantum machine learning are on full display. Finally, the technical and ethical difficulties of combining quantum machine learning with biomedical data are assessed in depth. The authors also provide an outlook on the promising interdisciplinary subject of quantum-powered machine learning and its potential to radically alter the field of biomedical research and healthcare solutions.
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