Date of Publication :8th August 2024

Abstract:Quantum computers are a new technology with a strong computational power to solve complicated issues. Quantum computing has evolved into strong tools for a wide range of application disciplines, including chemistry, agriculture, natural language processing, and healthcare, as computer power has increased exponentially and machine learning algorithms have advanced. When conventional data and machine learning methods are processed using quantum computing, new domains emerge, such as quantum machine learning. Quantum machine learning offers great performance and computational capabilities, making it helpful for solving computing jobs. Quantum machine learning has several use cases in the field of medical science. Quantum machine learning analyses and classifies massive datasets using quantum computing techniques and algorithms to detect invisible trends and forecast disease development or progression. This method has the potential to bring novel understandings into complicated biological systems, allowing for the creation of treatments that are more efficient and personalized. It allows medical professionals to diagnose diseases quickly and accurately. In this research, we examined the work done in the field of disease prediction in the biomedical domain using quantum machine learning by analyzing the research papers of various researchers, including the performance of each method and approach employed, as well as their accuracy.

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