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 >

Elias Hossain¹, Mohammed Alshehri², Sultan Almakdi^2,*, Hanan Halawani², Md. Mizanur Rahman³, Wahidur Rahman⁴, Sabila Al Jannat⁵, Nadim Kaysar⁶, Shishir Mia⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1713-1746, 2022, DOI:10.32604/cmc.2022.024822

Abstract Diabetes Mellitus is one of the most severe diseases, and many studies have been conducted to anticipate diabetes. This research aimed to develop an intelligent mobile application based on machine learning to determine the diabetic, pre-diabetic, or non-diabetic without the assistance of any physician or medical tests. This study's methodology was classified into two the Diabetes Prediction Approach and the Proposed System Architecture Design. The Diabetes Prediction Approach uses a novel approach, Light Gradient Boosting Machine (LightGBM), to ensure a faster diagnosis. The Proposed System Architecture Design has been combined into seven modules; the Answering Question Module is a natural… More >

Muhammad Anwar¹, Farhan Masud², Rizwan Aslam Butt³, Sevia Mahdaliza Idrus^4,*, Mohammad Nazir Ahmad⁵, Mohd Yazid Bajuri⁶

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4443-4456, 2022, DOI:10.32604/cmc.2022.022826

Abstract Wireless Body Area Sensor Network (WBASN) is an automated system for remote health monitoring of patients. WBASN under umbrella of Internet of Things (IoT) is comprised of small Biomedical Sensor Nodes (BSNs) that can communicate with each other without human involvement. These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs. The BSNs generate critical data as it is related to patient's health. The data traffic can be classified as Sensitive Data (SD) and Non-sensitive Data (ND) packets based on the value of vital signs. These data packets have… More >

Nithya Rekha Sivakumar^1,*, Ahmed Zohair Ibrahim²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4467-4483, 2022, DOI:10.32604/cmc.2022.019041

Abstract

Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational assistances. It makes an effort to get the better of issues of health service delivery involving time factor, space and laborious terrains, validating cost-efficiency and finer ingress in both developed and developing countries. Tele health has been categorized into either real-time electronic communication, or store-and-forward communication. In recent years, a third-class has been perceived as remote healthcare monitoring or tele health, presuming data obtained via Internet of Things (IOT). Although, tele health data analytics and machine learning have been researched in great depth, there… More >

Osama S. Faragallah^1,*, Ahmed I. Sallam², Hala S. El-sayed³

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 831-845, 2022, DOI:10.32604/cmc.2022.019151

Abstract Coronavirus (COVID-19) is a contagious disease that causes exceptional effect on healthcare organizations worldwide with dangerous impact on medical services within the hospitals. Because of the fast spread of COVID-19, the healthcare facilities could be a big source of disease infection. So, healthcare video consultations should be used to decrease face-to-face communication between clinician and patients. Healthcare video consultations may be beneficial for some COVID-19 conditions and reduce the need for face-to-face contact with a potentially positive patient without symptoms. These conditions are like top clinicians who provide remote consultations to develop treatment methodology and follow-up remotely, patients who consult… More >

Wenqian Li¹, Xing Deng^1,2,*, Haijian Shao¹, Xia Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 65-98, 2021, DOI:10.32604/cmes.2021.016981

Abstract The COVID-19 has resulted in catastrophic situation and the deaths of millions of people all over the world. In this paper, the predictions of epidemiological propagation models, such as SIR and SEIR, are introduced to analyze the earlier COVID-19 propagation. The deep learning methods combined with transfer learning are familiar with classification-detection approaches based on chest X-ray and CT images are presented in detail. Besides, deep learning approaches have also been applied to lung ultrasound (LUS), which has been shown to be more sensitive than chest X-ray and CT images in detecting COVID-19. In the absence of a vaccine, the… More > Graphic Abstract

Shada A. Alsalamah^1,2,3,*, Hessah A. Alsalamah^1,4, Thamer Nouh⁵, Sara A. Alsalamah⁶

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

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, we aim to study the… More >

Muhammad Arslan Usman^1,4,*, Muhammad Rehan Usman², Rizwan Ali Naqvi³, Bernie Mcphilips⁴, Christopher Romeika⁴, Daniel Cunliffe⁴, Christos Politis¹, Nada Philip¹

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 529-547, 2021, DOI:10.32604/cmc.2021.014614

Abstract Video compression in medical video streaming is one of the key technologies associated with mobile healthcare. Seamless delivery of medical video streams over a resource constrained network emphasizes the need of a video codec that requires minimum bitrates and maintains high perceptual quality. This paper presents a comparative study between High Efficiency Video Coding (HEVC) and its potential successor Versatile Video Coding (VVC) in the context of healthcare. A large-scale subjective experiment comprising of twenty-four non-expert participants is presented for eight different test conditions in Full High Definition (FHD) videos. The presented analysis highlights the impact of compression artefacts on… More >

Le Sun^1,*, Qiandi Yu¹, Dandan Peng¹, Sudha Subramani², Xuyang Wang¹

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 603-619, 2021, DOI:10.32604/cmc.2020.012515

Abstract Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor data streams, named FogMed. This… More >

Yihe Liu¹, Aaqif Afzaal Abbasi², Atefeh Aghaei³, Almas Abbasi⁴, Amir Mosavi^{5, 6, 7}, Shahaboddin Shamshirband^{8, 9, *}, Mohammed A. A. Al-qaness¹⁰

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 31-39, 2020, DOI:10.32604/cmc.2020.07708

Abstract Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace. Similarly, the field of health informatics is also considered as an extremely important field. This work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing analysis. The developed system has two front ends, the first dedicated for the user to perform the photographing of the trace report. Once the photographing is complete, mobile computing is used to extract the signal. Once the signal is extracted, it is uploaded into the… More >