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 >

Ala Saleh Alluhaidan^1,*, Pushparaj², Anitha Subbappa³, Ved Prakash Mishra⁴, P. V. Chandrika⁵, Anurika Vaish⁶, Sarthak Sengupta⁶

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5821-5836, 2023, DOI:10.32604/cmc.2023.033995

Abstract ESystems based on EHRs (Electronic health records) have been in use for many years and their amplified realizations have been felt recently. They still have been pioneering collections of massive volumes of health data. Duplicate detections involve discovering records referring to the same practical components, indicating tasks, which are generally dependent on several input parameters that experts yield. Record linkage specifies the issue of finding identical records across various data sources. The similarity existing between two records is characterized based on domain-based similarity functions over different features. De-duplication of one dataset or the linkage of multiple data sets has become… More >

Hanan T. Halawani^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6775-6788, 2023, DOI:10.32604/cmc.2023.030814

Abstract Biomedical image processing acts as an essential part of several medical applications in supporting computer aided disease diagnosis. Magnetic Resonance Image (MRI) is a commonly utilized imaging tool used to save glioma for clinical examination. Biomedical image segmentation plays a vital role in healthcare decision making process which also helps to identify the affected regions in the MRI. Though numerous segmentation models are available in the literature, it is still needed to develop effective segmentation models for BT. This study develops a salp swarm algorithm with multi-level thresholding based brain tumor segmentation (SSAMLT-BTS) model. The presented SSAMLT-BTS model initially employs… More >

K. Anuratha^1,*, M. Parvathy²

Computer Systems Science and Engineering, Vol.45, No.3, pp. 3005-3021, 2023, DOI:10.32604/csse.2023.031553

Abstract The COVID-19 pandemic has become one of the severe diseases in recent years. As it majorly affects the common livelihood of people across the universe, it is essential for administrators and healthcare professionals to be aware of the views of the community so as to monitor the severity of the spread of the outbreak. The public opinions are been shared enormously in microblogging media like twitter and is considered as one of the popular sources to collect public opinions in any topic like politics, sports, entertainment etc., This work presents a combination of Intensity Based Emotion Classification Convolution Neural Network… More >

S. Periyanayagi¹, V. Nandini^2,*, K. Basarikodi³, V. Sumathy⁴

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2853-2868, 2023, DOI:10.32604/csse.2023.030538

Abstract The Internet of Things (IoT) is a concept that refers to the deployment of Internet Protocol (IP) address sensors in health care systems to monitor patients’ health. It has the ability to access the Internet and collect data from sensors. Automated decisions are made after evaluating the information of illness people records. Patients’ health and well-being can be monitored through IoT medical devices. It is possible to trace the origins of biological, medical equipment and processes. Human reliability is a major concern in user activity and fitness trackers in day-to-day activities. The fundamental challenge is to measure the efficiency of… More >

P. M. Arunkumar¹, Mehedi Masud², Sultan Aljahdali², Mohamed Abouhawwash^3,4,*

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2265-2280, 2023, DOI:10.32604/csse.2023.032571

Abstract Nowadays, the cloud environment faces numerous issues like synchronizing information before the switch over the data migration. The requirement for a centralized internet of things (IoT)-based system has been restricted to some extent. Due to low scalability on security considerations, the cloud seems uninteresting. Since healthcare networks demand computer operations on large amounts of data, the sensitivity of device latency evolved among health networks is a challenging issue. In comparison to cloud domains, the new paradigms of fog computing give fresh alternatives by bringing resources closer to users by providing low latency and energy-efficient data processing solutions. Previous fog computing… 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 >

Hasanien K. Kuba¹, Mustafa A. Azzawi², Saad M. Darwish^3,*, Oday A. Hassen⁴, Ansam A. Abdulhussein⁵

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4119-4133, 2023, DOI:10.32604/cmc.2023.033182

Abstract It is crucial, while using healthcare data, to assess the advantages of data privacy against the possible drawbacks. Data from several sources must be combined for use in many data mining applications. The medical practitioner may use the results of association rule mining performed on this aggregated data to better personalize patient care and implement preventive measures. Historically, numerous heuristics (e.g., greedy search) and metaheuristics-based techniques (e.g., evolutionary algorithm) have been created for the positive association rule in privacy preserving data mining (PPDM). When it comes to connecting seemingly unrelated diseases and drugs, negative association rules may be more informative… More >

Marwan H. Hassan¹, Saad M. Darwish^2,*, Saleh M. Elkaffas³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4417-4434, 2023, DOI:10.32604/cmc.2023.033175

Abstract Electronic patient data gives many advantages, but also new difficulties. Deadlocks may delay procedures like acquiring patient information. Distributed deadlock resolution solutions introduce uncertainty due to inaccurate transaction properties. Soft computing-based solutions have been developed to solve this challenge. In a single framework, ambiguous, vague, incomplete, and inconsistent transaction attribute information has received minimal attention. The work presented in this paper employed type-2 neutrosophic logic, an extension of type-1 neutrosophic logic, to handle uncertainty in real-time deadlock-resolving systems. The proposed method is structured to reflect multiple types of knowledge and relations among transactions’ features that include validation factor degree, slackness… More >