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

作　　者：Iyad Katib Mahmoud Ragab 

机构地区：[1]Department of Computer Science,Faculty of Computing and Information Technology,King Abdulaziz University,Jeddah,21589,Saudi Arabia [2]Information Technology Department,Faculty of Computing and Information Technology,King Abdulaziz University,Jeddah,21589,Saudi Arabia

出　　处：《Computer Systems Science & Engineering》2023年第9期3749-3765,共17页计算机系统科学与工程（英文）

基　　金：This research work was funded by Institutional Fund Projects under grant no.(IFPIP:488-611-1443);Therefore,the authors gratefully acknowledge technical and financial support provided by Ministry of Education and Deanship of Scientific Research(DSR),King Abdulaziz University(KAU),Jeddah,Saudi Arabia.

摘　　要：The concept of smart healthcare has seen a gradual increase with the expansion of information technology.Smart 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 convenient.This work designs a new Heap Based Optimization with Deep Quantum Neural Network(HBO-DQNN)model for decision-making in smart healthcare applications.The presented HBO-DQNN modelmajorly focuses on identifying and classifying healthcare data.In the presented HBO-DQNN model,three stages of operations were performed.Data normalization is applied to pre-process the input data at the initial stage.Next,the HBO algorithm is used in the second stage to choose an optimal set of features from the healthcare data.At 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 model.The 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 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]