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  • Open Access

    ARTICLE

    Machine Learning Based Framework for Maintaining Privacy of Healthcare Data

    Adil Hussain Seh1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Alka Agrawal1, Rajeev Kumar4,*, Raees Ahmad Khan1

    Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 697-712, 2021, DOI:10.32604/iasc.2021.018048 - 01 July 2021

    Abstract The Adoption of Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), cloud services, web-based software systems, and other wireless sensor devices in the healthcare infrastructure have led to phenomenal improvements and benefits in the healthcare sector. Digital healthcare has ensured early diagnosis of the diseases, greater accessibility, and mass outreach in terms of treatment. Despite this unprecedented success, the privacy and confidentiality of the healthcare data have become a major concern for all the stakeholders. Data breach reports reveal that the healthcare data industry is one of the key targets of cyber invaders.… More >

  • Open Access

    ARTICLE

    Design and Experimentation of Causal Relationship Discovery among Features of Healthcare Datasets

    Y. Sreeraman*, S. Lakshmana Pandian

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 539-557, 2021, DOI:10.32604/iasc.2021.017256 - 16 June 2021

    Abstract Causal relationships in a data play vital role in decision making. Identification of causal association in data is one of the important areas of research in data analytics. Simple correlations between data variables reveal the degree of linear relationship. Partial correlation explains the association between two variables within the control of other related variables. Partial association test explains the causality in data. In this paper a couple of causal relationship discovery strategies are proposed using the design of partial association tree that makes use of partial association test among variables. These decision trees are different… More >

  • Open Access

    ARTICLE

    Competency Driven Resource Evaluation Method for Business Process Intelligence

    Abid Sohail1,*, Dhanapal Durai Dominic2, Mohammad Hijji3, Muhammad Arif Butt4

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1141-1157, 2021, DOI:10.32604/cmc.2021.018023 - 04 June 2021

    Abstract Enterprises are continuously aiming at improving the execution of processes to achieve a competitive edge. One of the established ways of improving process performance is to assign the most appropriate resources to each task of the process. However, evaluations of business process improvement approaches have established that a method that can guide decision-makers to identify the most appropriate resources for a task of process improvement in a structured way, is missing. It is because the relationship between resources and tasks is less understood and advancement in business process intelligence is also ignored. To address this More >

  • Open Access

    ARTICLE

    Design of an Efficient Cooperative Spectrum for Intra-Hospital Cognitive Radio Network

    Abhinav Adarsh1, Basant Kumar1, Manoj Gupta2, Arun Kumar2, Aman Singh3,*, Mehedi Masud4, Fahad A. Alraddady5

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 35-49, 2021, DOI:10.32604/cmc.2021.017647 - 04 June 2021

    Abstract This paper presents a new low delay centralized cooperative spectrum sensing method based on dynamic voting rule using multiple threshold level, for indoor hospital environment, where fading and direct path loss both are together responsible for variation in signal strength. In the proposed algorithm, weights of Cognitive Radios (CRs) in terms of assigned vote-count are estimated based on the sensed energy values with respect to multiple fixed threshold levels, so that the direct path loss can be dealt without further increasing the error, which occurs due to fading. For indoor hospital like environment, Rician fading More >

  • Open Access

    ARTICLE

    Leveraging Convolutional Neural Network for COVID-19 Disease Detection Using CT Scan Images

    Mehedi Masud*, Mohammad Dahman Alshehri, Roobaea Alroobaea, Mohammad Shorfuzzaman

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 1-13, 2021, DOI:10.32604/iasc.2021.016800 - 12 May 2021

    Abstract In 2020, the world faced an unprecedented pandemic outbreak of coronavirus disease (COVID-19), which causes severe threats to patients suffering from diabetes, kidney problems, and heart problems. A rapid testing mechanism is a primary obstacle to controlling the spread of COVID-19. Current tests focus on the reverse transcription-polymerase chain reaction (RT-PCR). The PCR test takes around 4–6 h to identify COVID-19 patients. Various research has recommended AI-based models leveraging machine learning, deep learning, and neural networks to classify COVID-19 and non-COVID patients from chest X-ray and computerized tomography (CT) scan images. However, no model can… More >

  • Open Access

    ARTICLE

    HealthyBlockchain for Global Patients

    Shada A. Alsalamah1,2,3,*, Hessah A. Alsalamah1,4, Thamer Nouh5, Sara A. Alsalamah6

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2431-2449, 2021, DOI:10.32604/cmc.2021.016618 - 13 April 2021

    Abstract An emerging healthcare delivery model is enabling a new era of clinical care based on well-informed decision-making processes. Current healthcare information systems (HISs) fall short of adopting this model due to a conflict between information security needed to implement the new model and those already enforced locally to support traditional care models. Meanwhile, in recent times, the healthcare sector has shown a substantial interest in the potential of using blockchain technology for providing quality care to patients. No blockchain solution proposed so far has fully addressed emerging cross-organization information-sharing needs in healthcare. In this paper, More >

  • Open Access

    ARTICLE

    Hyperledger Fabric Blockchain: Secure and Efficient Solution for Electronic Health Records

    Mueen Uddin1,*, M. S. Memon2, Irfana Memon2, Imtiaz Ali2, Jamshed Memon3, Maha Abdelhaq4, Raed Alsaqour5

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2377-2397, 2021, DOI:10.32604/cmc.2021.015354 - 13 April 2021

    Abstract Background: Electronic Health Record (EHR) systems are used as an efficient and effective technique for sharing patient’s health records among different hospitals and various other key stakeholders of the healthcare industry to achieve better diagnosis and treatment of patients globally. However, the existing EHR systems mostly lack in providing appropriate security, entrusted access control and handling privacy and secrecy issues and challenges in current hospital infrastructures. Objective: To solve this delicate problem, we propose a Blockchain-enabled Hyperledger Fabric Architecture for different EHR systems. Methodology: In our EHR blockchain system, Peer nodes from various organizations (stakeholders)… More >

  • Open Access

    ARTICLE

    Machine Learning Techniques Applied to Electronic Healthcare Records to Predict Cancer Patient Survivability

    Ornela Bardhi1,2,*, Begonya Garcia Zapirain1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1595-1613, 2021, DOI:10.32604/cmc.2021.015326 - 13 April 2021

    Abstract Breast cancer (BCa) and prostate cancer (PCa) are the two most common types of cancer. Various factors play a role in these cancers, and discovering the most important ones might help patients live longer, better lives. This study aims to determine the variables that most affect patient survivability, and how the use of different machine learning algorithms can assist in such predictions. The AURIA database was used, which contains electronic healthcare records (EHRs) of 20,006 individual patients diagnosed with either breast or prostate cancer in a particular region in Finland. In total, there were 178… More >

  • Open Access

    ARTICLE

    An End-to-End Authentication Scheme for Healthcare IoT Systems Using WMSN

    Shadi Nashwan*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 607-642, 2021, DOI:10.32604/cmc.2021.015597 - 22 March 2021

    Abstract The healthcare internet of things (IoT) system has dramatically reshaped this important industry sector. This system employs the latest technology of IoT and wireless medical sensor networks to support the reliable connection of patients and healthcare providers. The goal is the remote monitoring of a patient’s physiological data by physicians. Moreover, this system can reduce the number and expenses of healthcare centers, make up for the shortage of healthcare centers in remote areas, enable consultation with expert physicians around the world, and increase the health awareness of communities. The major challenges that affect the rapid… More >

  • Open Access

    ARTICLE

    Blockchain-as-a-Utility for Next-Generation Healthcare Internet of Things

    Alaa Omran Almagrabi1, Rashid Ali2, Daniyal Alghazzawi1, Abdullah AlBarakati1, Tahir Khurshaid3,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 359-376, 2021, DOI:10.32604/cmc.2021.014753 - 22 March 2021

    Abstract The scope of the Internet of Things (IoT) applications varies from strategic applications, such as smart grids, smart transportation, smart security, and smart healthcare, to industrial applications such as smart manufacturing, smart logistics, smart banking, and smart insurance. In the advancement of the IoT, connected devices become smart and intelligent with the help of sensors and actuators. However, issues and challenges need to be addressed regarding the data reliability and protection for significant next-generation IoT applications like smart healthcare. For these next-generation applications, there is a requirement for far-reaching privacy and security in the IoT.… More >

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