Mathematical Modelling of Quantum Kernel Method for Biomedical Data Analysis
نویسندگان
چکیده
This study presents a novel method to detect the medical application based on Quantum Computing (QC) and few Machine Learning (ML) systems. QC has primary advantage i.e., it uses impact of quantum parallelism provide consequences prime factorization issue in matter seconds. So, this model is suggested for only by recent researchers. A strategy Kernel Method (QKM) proposed paper data prediction. In QKM process, Linear Tunicate Swarm Algorithm (LTSA), optimization technique used calculate loss function initially aimed at data. The output either 0 or 1 odd even QC. From value, identified according class. Meanwhile, also reduces time, saves cost improves efficiency feature selection process Filter method. After features are extracted, deployed as classification model, while minimized LTSA. motivation minimal objective remain faster. However, some computations can be performed more efficiently model. testing, test was evaluated function. outcomes were assessed terms accuracy, computational so on. For this, databases like Lymphography, Dermatology, Arrhythmia used.
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ژورنال
عنوان ژورنال: Computers, materials & continua
سال: 2022
ISSN: ['1546-2218', '1546-2226']
DOI: https://doi.org/10.32604/cmc.2022.024545