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Heap Based Optimization with Deep Quantum Neural Network Based Decision Making on Smart Healthcare Applications

Computer Systems Science & Engineering 2023年第9期46卷 3749-3765页

作者： iyad katib Mahmoud Ragab Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia

The concept of smart healthcare has seen a gradual increase with the expansion of information *** healthcare will use a new generation of information technologies,like artificial intelligence,the Internet of Things(IoT),cloud computing,and big data,to transformthe conventional medical system in an all-around way,making healthcare highly effective,more personalized,and more *** work designs a new Heap Based Optimization with Deep Quantum Neural Network(HBO-DQNN)model for decision-making in smart healthcare *** presented HBO-DQNN modelmajorly focuses on identifying and classifying healthcare *** the presented HBO-DQNN model,three stages of operations were *** normalization is applied to pre-process the input data at the initial ***,the HBO algorithm is used in the second stage to choose an optimal set of features from the healthcare *** last,the DQNN model is exploited for healthcare data classification.A series of experiments were carried out to portray the promising classifier results of the HBO-DQNN *** extensive comparative study reported the improvements of the HBO-DQNN method over other existing models with maximum accuracy of 97.05%and 95.72%under the colon cancer and lymphoma dataset.

关键词： Heap-based optimization smart healthcare decision making intelligent models artificial intelligence

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