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  • Open Access

    ARTICLE

    Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

    K. Akilandeswari1, Nithya Rekha Sivakumar2,*, Hend Khalid Alkahtani3, Shakila Basheer3, Sara Abdelwahab Ghorashi2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1189-1205, 2024, DOI:10.32604/cmc.2023.034815

    Abstract In this present time, Human Activity Recognition (HAR) has been of considerable aid in the case of health monitoring and recovery. The exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and significance. Although many research works conducted on Smart Healthcare Monitoring, there remain a certain number of pitfalls such as time, overhead, and falsification involved during analysis. Therefore, this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning (SPR-SVIAL) for Smart Healthcare Monitoring. At first, the Statistical Partial Regression Feature Extraction model is used… More >

  • Open Access

    ARTICLE

    Advance IoT Intelligent Healthcare System for Lung Disease Classification Using Ensemble Techniques

    J. Prabakaran1,*, P. Selvaraj2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2141-2157, 2023, DOI:10.32604/csse.2023.034210

    Abstract In healthcare systems, the Internet of Things (IoT) innovation and development approached new ways to evaluate patient data. A cloud-based platform tends to process data generated by IoT medical devices instead of high storage, and computational hardware. In this paper, an intelligent healthcare system has been proposed for the prediction and severity analysis of lung disease from chest computer tomography (CT) images of patients with pneumonia, Covid-19, tuberculosis (TB), and cancer. Firstly, the CT images are captured and transmitted to the fog node through IoT devices. In the fog node, the image gets modified into a convenient and efficient format… More >

  • Open Access

    ARTICLE

    Explainable Anomaly Detection Using Vision Transformer Based SVDD

    Ji-Won Baek1, Kyungyong Chung2,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6573-6586, 2023, DOI:10.32604/cmc.2023.035246

    Abstract Explainable AI extracts a variety of patterns of data in the learning process and draws hidden information through the discovery of semantic relationships. It is possible to offer the explainable basis of decision-making for inference results. Through the causality of risk factors that have an ambiguous association in big medical data, it is possible to increase transparency and reliability of explainable decision-making that helps to diagnose disease status. In addition, the technique makes it possible to accurately predict disease risk for anomaly detection. Vision transformer for anomaly detection from image data makes classification through MLP. Unfortunately, in MLP, a vector… More >

  • Open Access

    ARTICLE

    A Robust Data Hiding Reversible Technique for Improving the Security in e-Health Care System

    Saima Kanwal1, Feng Tao1,*, Ahmad Almogren2, Ateeq Ur Rehman3, Rizwan Taj1, Ayman Radwan4

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 201-219, 2023, DOI:10.32604/cmes.2022.020255

    Abstract The authenticity and integrity of healthcare is the primary objective. Numerous reversible watermarking schemes have been developed to improve the primary objective but increasing the quantity of embedding data leads to covering image distortion and visual quality resulting in data security detection. A trade-off between robustness, imperceptibility, and embedded capacity is difficult to achieve with current algorithms due to limitations in their ability. Keeping this purpose insight, an improved reversibility watermarking methodology is proposed to maximize data embedding capacity and imperceptibility while maintaining data security as a primary concern. A key is generated by a random path with minimum bit… More >

  • Open Access

    ARTICLE

    Ensemble Deep Learning for IoT Based COVID 19 Health Care Pollution Monitor

    Nithya Rekha Sivakumar*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2383-2398, 2023, DOI:10.32604/iasc.2023.028574

    Abstract Internet of things (IoT) has brought a greater transformation in healthcare sector thereby improving patient care, minimizing treatment costs. The present method employs classical mechanisms for extracting features and a regression model for prediction. These methods have failed to consider the pollution aspects involved during COVID 19 prediction. Utilizing Ensemble Deep Learning and Framingham Feature Extraction (FFE) techniques, a smart healthcare system is introduced for COVID-19 pandemic disease diagnosis. The Collected feature or data via predictive mechanisms to form pollution maps. Those maps are used to implement real-time countermeasures, such as storing the extracted data or feature in a Cloud… More >

  • Open Access

    ARTICLE

    Hybrid Smart Contracts for Securing IoMT Data

    D. Palanikkumar1, Adel Fahad Alrasheedi2, P. Parthasarathi3, S. S. Askar2, Mohamed Abouhawwash4,5,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 457-469, 2023, DOI:10.32604/csse.2023.024884

    Abstract Data management becomes essential component of patient healthcare. Internet of Medical Things (IoMT) performs a wireless communication between E-medical applications and human being. Instead of consulting a doctor in the hospital, patients get health related information remotely from the physician. The main issues in the E-Medical application are lack of safety, security and privacy preservation of patient’s health care data. To overcome these issues, this work proposes block chain based IoMT Processed with Hybrid consensus protocol for secured storage. Patients health data is collected from physician, smart devices etc. The main goal is to store this highly valuable health related… More >

  • Open Access

    ARTICLE

    Internet of Things for in Home Health Based Monitoring System: Modern Advances, Challenges and Future Directions

    Omer Iqbal*, Tayyeba Iftakhar, Saleem Zubair Ahmad

    Journal on Internet of Things, Vol.4, No.1, pp. 35-55, 2022, DOI:10.32604/jiot.2022.022256

    Abstract IOT has carried out important function in converting the traditional fitness care corporation. With developing call for in population, traditional healthcare structures have reached their outmost functionality in presenting sufficient and as plenty as mark offerings. The worldwide is handling devastating developing antique population disaster and the right want for assisted-dwelling environments is turning into inevitable for senior citizens. There furthermore a determination by means of the use of way of countrywide healthcare organizations to increase crucial manual for individualized, right blanketed care to prevent and manipulate excessive coronial situations. Many tech orientated packages related to Health Monitoring have been… More >

  • Open Access

    ARTICLE

    Crypto Hash Based Malware Detection in IoMT Framework

    R Punithavathi1, K Venkatachalam2, Mehedi Masud3, Mohammed A. AlZain4, Mohamed Abouhawwash5,6,*

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 559-574, 2022, DOI:10.32604/iasc.2022.024715

    Abstract The challenges in providing e-health services with the help of Internet of Medical Things (IoMT) is done by connecting to the smart medical devices. Through IoMT sensor devices/smart devices, physicians share the sensitive information of the patient. However, protecting the patient health care details from malware attack is necessary in this advanced digital scenario. Therefore, it is needed to implement cryptographic algorithm to enhance security, safety, reliability, preventing details from malware attacks and privacy of medical data. Nowadays blockchain has become a prominent technology for storing medical data securely and transmit through IoMT concept. The issues in the existing research… More >

  • Open Access

    ARTICLE

    Cost Efficient Scheduling Using Smart Contract Cognizant Ethereum for IoMT

    G. Ravikumar1, K. Venkatachalam2, Mehedi Masud3, Mohamed Abouhawwash4,5,*

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 865-877, 2022, DOI:10.32604/iasc.2022.024278

    Abstract Recently internet of medical things (IoMT) act as a smart doctor using sensor wearable’s device in human body. This smart doctor device senses necessary medical data from human and transfer via network immediately to physician. It is important to transfer sensitive data very securely. Blockchain becomes trending technology to provide high security to both end users in the network. Traditionally security structure is relying on cryptographic techniques which is very expensive and takes more time in securely transmitting data. To overcome this issue, this paper builds a cost effective, blockchain with IoMT using fog-cloud computing. The aim of research is… More >

  • Open Access

    ARTICLE

    Closing the Gap: Characterizing Key Factors Leading to the Disparity in Suicide Rates along the Urban-Rural Continuum

    Harrison Schurr, Andrei Tuluca*, Beth Bailey

    International Journal of Mental Health Promotion, Vol.24, No.2, pp. 159-167, 2022, DOI:10.32604/ijmhp.2022.017990

    Abstract Suicide is a top ten cause of mortality in the United States. In previous literature the suicide rates in rural communities have been reported to be greater than those of more urban communities. Additionally, these studies have discussed many potential causes for the unfortunate disparity in rates. One cause often discussed is lack of mental health care providers in rural communities. The data for this study was gathered from the CDC’s WONDER database and the NPPES NPI Registry. The urban-rural categorization of counties used the 2013 NCHS Urban-Rural Scheme. Statistical analysis included chi-square tests, paired t-tests, and stepwise regression analyses.… More >

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