J. Prabakaran^1,*, 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 >

Sarah B. Basahel¹, Saleh Bajaba², Mohammad Yamin³, Sachi Nandan Mohanty⁴, E. Laxmi Lydia^5,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1353-1369, 2023, DOI:10.32604/cmc.2023.036453

Abstract The current advancement in cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT) transformed the traditional healthcare system into smart healthcare. Healthcare services could be enhanced by incorporating key techniques like AI and IoT. The convergence of AI and IoT provides distinct opportunities in the medical field. Fall is regarded as a primary cause of death or post-traumatic complication for the ageing population. Therefore, earlier detection of older person falls in smart homes is required to improve the survival rate of an individual or provide the necessary support. Lately, the emergence of IoT, AI, smartphones, wearables, and so… More >

Sathya Bama B^*, Bevish Jinila Y

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2085-2097, 2023, DOI:10.32604/iasc.2023.028481

Abstract Parkinson’s disease is identified as one of the key neurodegenerative disorders occurring due to the damages present in the central nervous system. The cause of such brain damage seems to be fully explained in many research studies, but the understanding of its functionality remains to be impractical. Specifically, the development of a quantitative disease prediction model has evolved in recent decades. Moreover, accelerometer sensor-based gait analysis is accepted as an important tool for recognizing the walking behavior of the patients during the early prediction and diagnosis of Parkinson’s disease. This type of minimal infrastructure equipment helps in analyzing the Parkinson’s… More >

Fawad Naseer^1,*, Muhammad Nasir Khan¹, Zubair Nawaz², Qasim Awais³

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6623-6639, 2023, DOI:10.32604/cmc.2023.035218

Abstract In this era of post-COVID-19, humans are psychologically restricted to interact less with other humans. According to the world health organization (WHO), there are many scenarios where human interactions cause severe multiplication of viruses from human to human and spread worldwide. Most healthcare systems shifted to isolation during the pandemic and a very restricted work environment. Investigations were done to overcome the remedy, and the researcher developed different techniques and recommended solutions. Telepresence robot was the solution achieved by all industries to continue their operations but with almost zero physical interaction with other humans. It played a vital role in… More >

Waleed T. Al-Sit¹, Nidal A. Al-Dmour², Taher M. Ghazal^3,4,*, Ghassan F. Issa³

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6867-6878, 2023, DOI:10.32604/cmc.2023.034952

Abstract In the age of universal computing, human life is becoming smarter owing to the recent developments in the Internet of Medical Things (IoMT), wearable sensors, and telecommunication innovations, which provide more effective and smarter healthcare facilities. IoMT has the potential to shape the future of clinical research in the healthcare sector. Wearable sensors, patients, healthcare providers, and caregivers can connect through an IoMT network using software, information, and communication technology. Ambient assisted living (AAL) allows the incorporation of emerging innovations into the routine life events of patients. Machine learning (ML) teaches machines to learn from human experiences and to use… More >

Sharmilee Kannan^1,*, R. U. Anitha², M. Divayapushpalakshmi³, K. S. Kalaivani⁴

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2001-2016, 2023, DOI:10.32604/csse.2023.031965

Abstract The rising use of mobile technology and smart gadgets in the field of health has had a significant impact on the global community. Health professionals are increasingly making use of the benefits of these technologies, resulting in a major improvement in health care both in and out of clinical settings. The Internet of Things (IoT) is a new internet revolution that is a rising research area, particularly in health care. Healthcare Monitoring Systems (HMS) have progressed rapidly as the usage of Wearable Sensors (WS) and smartphones have increased. The existing framework of conventional telemedicine’s store-and-forward method has some issues, including… More >

Muhammad Attique Khan¹, Majed Alhaisoni², Muhammad Nazir¹, Abdullah Alqahtani³, Adel Binbusayyis³, Shtwai Alsubai³, Yunyoung Nam⁴, Byeong-Gwon Kang^4,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1393-1412, 2023, DOI:10.32604/cmc.2023.032064

Abstract The coronavirus (COVID19), also known as the novel coronavirus, first appeared in December 2019 in Wuhan, China. After that, it quickly spread throughout the world and became a disease. It has significantly impacted our everyday lives, the national and international economies, and public health. However, early diagnosis is critical for prompt treatment and reducing trauma in the healthcare system. Clinical radiologists primarily use chest X-rays, and computerized tomography (CT) scans to test for pneumonia infection. We used Chest CT scans to predict COVID19 pneumonia and healthy scans in this study. We proposed a joint framework for prediction based on classical… More >

Ahyoung Lee¹, Jui Mhatre¹, Rupak Kumar Das², Min Hong^3,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 435-452, 2023, DOI:10.32604/cmc.2023.029340

Abstract Healthcare is a fundamental part of every individual’s life. The healthcare industry is developing very rapidly with the help of advanced technologies. Many researchers are trying to build cloud-based healthcare applications that can be accessed by healthcare professionals from their premises, as well as by patients from their mobile devices through communication interfaces. These systems promote reliable and remote interactions between patients and healthcare professionals. However, there are several limitations to these innovative cloud computing-based systems, namely network availability, latency, battery life and resource availability. We propose a hybrid mobile cloud computing (HMCC) architecture to address these challenges. Furthermore, we… More >

C. Santhosh Kumar¹, K. Vishnu Kumar^2,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2893-2907, 2023, DOI:10.32604/iasc.2023.029669

Abstract Privacy-preserving online disease prediction and diagnosis are critical issues in the emerging edge-cloud-based healthcare system. Online patient data processing from remote places may lead to severe privacy problems. Moreover, the existing cloud-based healthcare system takes more latency and energy consumption during diagnosis due to offloading of live patient data to remote cloud servers. Solve the privacy problem. The proposed research introduces the edge-cloud enabled privacy-preserving healthcare system by exploiting additive homomorphic encryption schemes. It can help maintain the privacy preservation and confidentiality of patients’ medical data during diagnosis of Parkinson’s disease. In addition, the energy and delay aware computational offloading… More >

Sumbal Khalil¹, Sajida Kousar¹, Nasreen Kausar², Muhammad Imran³, Georgia Irina Oros^4,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6207-6224, 2022, DOI:10.32604/cmc.2022.030547

Abstract Bipolar Interval-valued neutrosophic set is another generalization of fuzzy set, neutrosophic set, bipolar fuzzy set and bipolar neutrosophic set and thus when applied to the optimization problem handles uncertain data more efficiently and flexibly. Current work is an effort to design a flexible optimization model in the backdrop of interval-valued bipolar neutrosophic sets. Bipolar interval-valued neutrosophic membership grades are picked so that they indicate the restriction of the plausible infringement of the inequalities given in the problem. To prove the adequacy and effectiveness of the method a unified system of sustainable medical healthcare supply chain model with an uncertain figure… More >