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Enhancing healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart healthcare Systems

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 977-997页

作者： Mustufa Haider Abidi Hisham Alkhalefah Mohamed K.Aboudaif Department of Industrial Engineering College of EngineeringKing Saud UniversityP.O.Box-800Riyadh11421Saudi Arabia

The healthcare data requires accurate disease detection analysis,real-timemonitoring,and advancements to ensure proper treatment for ***,Machine Learning methods are widely utilized in Smart healthcare Systems(SHS)to extract valuable features fromheterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient *** methods are employed across different domains that are susceptible to adversarial attacks,necessitating careful ***,this paper proposes a crossover-based Multilayer Perceptron(CMLP)*** collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on themedical records of *** an attack is detected,healthcare professionals are promptly alerted to prevent data *** paper utilizes two datasets,namely the synthetic dataset and the University of Queensland Vital Signs(UQVS)dataset,from which numerous samples are *** results are conducted to evaluate the performance of the proposed CMLP model,utilizing various performancemeasures such as Recall,Precision,Accuracy,and F1-score to predict patient *** the proposed method with existing approaches,it achieves the highest accuracy,precision,recall,and ***,the proposedmethod achieves a precision of 93%,an accuracy of 97%,an F1-score of 92%,and a recall of 92%.

关键词： Smart healthcare systems multilayer perceptron cybersecurity adversarial attack detection healthcare 4.0

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