计算机科学
启发式
医疗保健
密码学
精确性和召回率
量子计算机
数据挖掘
机器学习
算法
人工智能
量子
物理
量子力学
经济
经济增长
作者
Hirak Mazumdar,Chinmay Chakraborty,Satheesh Bojja Venkatakrishnan,Ajeet Kaushik,Hardik Gohel
标识
DOI:10.1109/jbhi.2023.3304326
摘要
People's health is adversely affected by environmental changes and poor nutritional habits, emphasizing the importance of health awareness. The healthcare system encounters significant challenges, including data insufficiency, threats, errors, and delays. To address these issues and advance medical care, we propose a secure healthcare prediction method, prioritizing patient privacy and data transmission efficiency. The Quantum-inspired heuristic algorithm combined with Kril Herd Optimization (QKHO) is introduced for healthcare prediction, along with a comparison to the Deep Forward Neural Network (DFNN) optimized using Krill Herd Optimization (KHO) and Quantum-inspired heuristic algorithm combined with Kril Herd Optimization. The proposed QKHO model outperforms conventional models and exhibits higher accuracy, precision, recall, and F1-score. Blockchain technology ensures secure data transmission to the server, surpassing the security level of existing RSA and Diffie-Hellman algorithms.
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