Machine learning-data mining integrated approach for premature ventricular contraction prediction

Mastoi, Qurat-ul-ain; Memon, Muhammad Suleman; Lakhan, Abdullah; Mohammed, Mazin Abed; Qabulio, Mumtaz; Al‐Turjman, Fadi; Abdulkareem, Karrar Hameed

doi:10.1007/s00521-021-05820-2

Cited by 21 publications

(10 citation statements)

References 66 publications

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“…Tables 7 and 8 list the number of DWT and IDWT calls and their time ratio to the whole scheme, respectively. The time complexity of DWT is O M 2 L where M represents the size of the image and L represents the length of the filter [55][56][57][58][59][60]. The extraction process is the same as the embedding process that almost all of the time is spent on DWT and IDWT.…”

Section: Complexity Analysismentioning

confidence: 99%

A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness

Zhou

Zhang

et al. 2021

Electronics

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The authenticity and integrity of medical images in telemedicine has to be protected. Robust reversible watermarking (RRW) algorithms provide copyright protection and the original images can be recovered at the receiver’s end. However, the existing algorithms have limitations in their ability to balance the tradeoff among robustness, imperceptibility, and embedded capacity. Some of them are even not completely reversible. Besides, most medical image watermarking algorithms are not designed for color images. To improve their performance in protecting medical color image information, we propose a novel RRW scheme based on the discrete wavelet transform (DWT). First, the DWT provides a robust solution. Second, the modification of the wavelet domain coefficient guarantees the changes of integer values in the spatial domain and ensures the reversibility of the watermarking scheme. Third, the embedding scheme makes full use of the characteristics of the original image and watermarking. This reduces the modification of the original image and ensures better imperceptibility. Lastly, the selection of the Zernike moments order for geometric correction is optimized to predict attack parameters more accurately by using less information. This enhances the robustness of the proposed scheme against geometric attacks such as rotation and scaling. The proposed scheme is robust against common and geometric attacks and has a high embedding capacity without obvious distortion of the image. The paper contributes towards improving the security of medical images in remote healthcare.

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Section: Complexity Analysismentioning

confidence: 99%

A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness

Zhou

Zhang

et al. 2021

Electronics

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“…The studies [6][7][8] devised dynamic and secure IoMT systems based on different primitives such as workflow applications, deadlines, Genetic Algorithm (GA) on virtual machines (VMs), which enable cloud data centers, and RSA-based networks. The purpose of these studies is to gain dynamic results for healthcare applications in distributed cloud data centers.…”

Section: Related Workmentioning

confidence: 99%

“…Constraint (8) shows all the requested workloads of applications that must not exceed the limits of resources during execution.…”

Section: Iomt Tasks Sensorsmentioning

confidence: 99%

“…However, they execute onto geographically distributed network [7]. One of the main concerns is resource-constraint issues in devices (e.g., limited storage, small CPU, and short bandwidth utilization) and cannot execute applications locally [8]. Offloading is a way that migrates compute-intensive tasks of applications to distributed computing nodes for further execution via wireless technologies (e.g., WiFi, LTE, and others).…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, developers of serverless applications are not concerned with the container, VM, or physical server capacity planning, configuration, management, maintenance, fault tolerance, or scaling. In the literature, many studies [2,3,5,7,8,11,12] proposed different systems, architectures, and heuristicsbased IoMT network to solve the offloading and scheduling problem of workflow and fine-grained applications. These studies improved devices' battery lives, offloading cost and the obtained Service Level Agreement (SLA) and Quality of Service (QoS) applications during their problem formulation.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network

et al. 2021

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The Internet of Medical Things (IoMT) workflow applications have been rapidly growing in practice. These internet-based applications can run on the distributed healthcare sensing system, which combines mobile computing, edge computing and cloud computing. Offloading and scheduling are the required methods in the distributed network. However, a security issue exists and it is hard to run different types of tasks (e.g., security, delay-sensitive, and delay-tolerant tasks) of IoMT applications on heterogeneous computing nodes. This work proposes a new healthcare architecture for workflow applications based on heterogeneous computing nodes layers: an application layer, management layer, and resource layer. The goal is to minimize the makespan of all applications. Based on these layers, the work proposes a secure offloading-efficient task scheduling (SEOS) algorithm framework, which includes the deadline division method, task sequencing rules, homomorphic security scheme, initial scheduling, and the variable neighbourhood searching method. The performance evaluation results show that the proposed plans outperform all existing baseline approaches for healthcare applications in terms of makespan.

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Heart Disease Prediction Desktop Application Using Supervised Learning

Pattabiraman

Parvathi

2023

EAI/Springer Innovations in Communication and Computing

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Machine learning-data mining integrated approach for premature ventricular contraction prediction

Cited by 21 publications

References 66 publications

A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness

A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness

Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network

Heart Disease Prediction Desktop Application Using Supervised Learning

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