International Journal of E-Health and Medical Communications This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Classifier Selection for the Prediction of Dominant Transmission Mode of Coronavirus within Localities
The coronavirus disease-2019 (COVID-19) pandemic is an ongoing concern that requires research in all disciplines to tame its spread. Nine classification algorithms were selected for evaluating the most appropriate in predicting the prevalent COVID-19 transmission mode in a geographic area. These include; multinomial logistic regression, k-nearest neighbour, support vector machines, linear discriminant analysis, na ïve Bayes, C5.0, bagged classification and regression trees, random forest, and stochastic gradient boosting. Five COVID-19 datasets were employed for classification. Predictive accuracy was determined using 10-...
Source: International Journal of E-Health and Medical Communications - February 27, 2021 Category: Information Technology Tags: Health Information Systems Medicine & Healthcare Source Type: research

ADDietCoach - A Personalized Virtual Diet Coach for Alzheimer ’s Disease
The aging population worldwide is expected to increase the prevalence of Alzheimer ’s disease. As there is no medical curative treatment for this disease to date, alternative treatments have been applied to improve the patient’s brain and general health. One of these efforts includes providing Alzheimer’s patients with proper food and nutrition. In this paper, we propose a k nowledge-powered personalized virtual coach to provide diet and nutrition assistance to patients of Alzheimer’s and/or their informal caregivers. The virtual coach is built on top of an ontology-enhanced knowledge base containing knowledge abou...
Source: International Journal of E-Health and Medical Communications - February 27, 2021 Category: Information Technology Tags: Health Information Systems Medicine & Healthcare Source Type: research

The Healing Hearts at Home © Mobile Application Usability and Influence on Parental Perceived Stress
In this study, the Healing Hearts and Home © (HHH©) application was piloted to determine the usability and usefulness of the mobile application and whether the application had an effect on caregivers' coping and stress. A posttest consisting of the Systems Usability Scale (SUS), the Coping Health Inventory for Parents (CHIP), and the Perce ived Stress Scale (PSS) was used to collect information on the application usability, coping patterns, and perceived stress. Key informants provided more insight into usefulness. The SUS rating was 86.94 (SD = 6.34). The excellent usability score did not translate into uptake, though i...
Source: International Journal of E-Health and Medical Communications - January 18, 2021 Category: Information Technology Authors: Miller, Vanessa Ayer Newcombe, Jennifer Radovich, Patricia Johnston, Flint Medina Jr., Ernesto Nelson, Anna Tags: Health Information Systems Medicine & Healthcare Source Type: research

Study of Healthcare Annotation Systems
The annotation practice is an almost daily activity used by healthcare professionals (PHC) to analyze patients' records, collaborate, share knowledge, and communicate. These annotations are generated within a healthcare cycle. Similarly, this cycle represents the life cycle of annotations in the patient record. The exponential increase in the number of medical annotation systems made the choice of a system by a PHC difficult, in a well-defined context (biology, radiology) and according to his/her needs to the functionalities offered by these tools. Therefore, the authors propose two taxonomies to distinguish annotation too...
Source: International Journal of E-Health and Medical Communications - January 18, 2021 Category: Information Technology Authors: Chehab, Khalil Kalboussi, Anis Kacem, Ahmed Hadj Tags: Health Information Systems Medicine & Healthcare Source Type: research

Towards Better Segmentation of Abnormal Part in Multimodal Images Using Kernel Possibilistic C Means Particle Swarm Optimization With Morphological Reconstruction Filters
The authors designed an automated framework to segment tumors with various image sequences like T1, T2, and post-processed MRI multimodal images. Contrast-limited adaptive histogram equalization method is used for preprocessing images to enhance the intensity level and view the tumor part clearly. With the combination of kernel possibilistic c means clustering with particle swarm optimization technique, a tumor part is segmented, and morphological filters are applied to remove the unrelated outlier pixels in the segmented image to detect the accurate tumor part. The authors collected various image sequences from online res...
Source: International Journal of E-Health and Medical Communications - January 18, 2021 Category: Information Technology Authors: Sumathi R., Mandadi, Venkatesulu Tags: Health Information Systems Medicine & Healthcare Source Type: research

The Impact of Fractional-Order Control on Blood Pressure Regulation
This paper presents a fractional-order framework for control of blood pressure regulation system. A new perspective is explored to control the blood pressure in lieu of the conventional control framework. A multi-variable scenario is adopted to control two outputs: mean arterial blood pressure (MABP) and cardiac output (CO) simultaneously. Three fractional-order controllers are designed and tuned optimally for the multi-input multi-output (MIMO) blood pressure regulation system. To test the effectiveness of the designed fractional controllers, control investigations are carried out based on controller performance indices a...
Source: International Journal of E-Health and Medical Communications - January 18, 2021 Category: Information Technology Authors: Nagarsheth, Shaival H. Sharma, Shambhu N. Tags: Health Information Systems Medicine & Healthcare Source Type: research

Photoplethysmography Heart Rate Monitoring
Research conducted by the World Health Organisation (WHO) in 2018 demonstrated that the worldwide threat of cardiovascular diseases (CVDs) has increased compared to previous years. CVDs are very dangerous: if timely treatment is not performed, these conditions could become irreversible and lead to sudden death. Prescriptive measures include physical exercises and monitoring of the heart rate (HR). Despite the existence of various HR monitoring devices (or HMDs), a major challenge remains their availability, particularly to people in lower-income countries. Unfortunately, it is also this segment of the population that is th...
Source: International Journal of E-Health and Medical Communications - January 18, 2021 Category: Information Technology Authors: Feukeu, Etienne Alain Winberg, Simon Tags: Health Information Systems Medicine & Healthcare Source Type: research

Regulations and Standards Aware Framework for Recording of mHealth App Vulnerabilities
The authors describe a standards-based security framework for the purposes of recording security and privacy vulnerabilities discovered in mHealth apps. The proposed framework is compliant with the international standard for software architecture descriptions, ISO/IEC/IEEE 42010, relevant state-agency regulations, and US federal healthcare mandates, as well as computing standards for data interchange formats. Future real-life implementations are envisioned to consists of three key components: (1) design and implementation of a repository that links vulnerabilities to concepts from the taxonomy used by legislative and stand...
Source: International Journal of E-Health and Medical Communications - January 18, 2021 Category: Information Technology Authors: Prodanoff, Zornitza White-Williams, Cynthia Chi, Hongmei Tags: Health Information Systems Medicine & Healthcare Source Type: research

Advanced Object Detection in Bio-Medical X-Ray Images for Anomaly Detection and Recognition
The human vision system is mimicked in the format of videos and images in the area of computer vision. As humans can process their memories, likewise video and images can be processed and perceptive with the help of computer vision technology. There is a broad range of fields that have great speculation and concepts building in the area of application of computer vision, which includes automobile, biomedical, space research, etc. The case study in this manuscript enlightens one about the innovation and future scope possibilities that can start a new era in the biomedical image-processing sector. A pre-surgical investigatio...
Source: International Journal of E-Health and Medical Communications - December 1, 2020 Category: Information Technology Authors: Modwel, Garv Mehra, Anu Rakesh, Nitin Mishra, K. K. Tags: Health Information Systems Medicine & Healthcare Source Type: research

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One knows that smart transport is also an integrated part of healthcare technologies. To minimize the pollution for benefiting the healthcare, the traffic throughput on roundabout intersection has to be increased which will reduce wasted time and will also enhance passenger comfort. This paper presents a new approach by use of cooperative vehicular control utilizing VANET without compromising the safety of vehicles. This intersection side unit (ISU)-based system use lane change mechanism. The modular use of lane with lane change in newly designed protocol CARA (collision avoidance at roundabout algorithm) will greatly enha...
Source: International Journal of E-Health and Medical Communications - December 1, 2020 Category: Information Technology Authors: Vats, Hitender Tomar, Ranjeet Singh Tags: Health Information Systems Medicine & Healthcare Source Type: research

Prediction of Environmental Pollution Using Hybrid PSO-K-Means Approach
Air pollution is increasing day by day, decreasing the world economy, degrading the quality of life, and resulting in a major productivity loss. At present, this is one of the most critical problems. It has a significant impact on human health and ecosystem. Reliable air quality prediction can reduce the impact it has on the nearby population and ecosystem; hence, improving air quality prediction is the prime objective for the society. The air quality data collected from sensors usually contains deviant values called outliers which have a significant detrimental effect on the quality of prediction and need to be detected a...
Source: International Journal of E-Health and Medical Communications - December 1, 2020 Category: Information Technology Authors: Mahajan, Manish Kumar, Santosh Pant, Bhasker Tags: Health Information Systems Medicine & Healthcare Source Type: research

Lung Tumor Segmentation Using Marker-Controlled Watershed and Support Vector Machine
The medical imaging technique showed remarkable improvement in interventional treatment of computer-aided medical diagnosis system. Image processing techniques are broadly applied in detection and exploring the abnormalities issues in tumor detection. The early stage of lung tumor detection is extremely important in medical research field. The proposed work uses image processing segmentation technique for detection of lung tumor and the support vector classifier learning technique for predicting stage of tumor. After performing preprocessing and segmentation the features are extracted from region of lung nodule. The classi...
Source: International Journal of E-Health and Medical Communications - December 1, 2020 Category: Information Technology Authors: Vijh, Surbhi Sarma, Rituparna Kumar, Sumit Tags: Health Information Systems Medicine & Healthcare Source Type: research

Artificial Bee Colony and Deep Neural Network-Based Diagnostic Model for Improving the Prediction Accuracy of Diabetes
In this study, an effort is made to design an automated diagnostic model for the diagnosis and prediction of diabetes patients. The proposed diagnostic model is designed using artificial bee colony (ABC) algorithm and deep neural network (DNN) technique, called ABC-DNN-based diagnostic model. The ABC algorithm is applied to determine the relevant features for diabetes prediction and diagnosis while DNN technique is adopted for the prediction and diagnosis of diabetes affected patients. The performance of proposed diagnostic model is tested over Pima Indian Diabetes dataset and evaluated using accuracy, sensitivity, specifi...
Source: International Journal of E-Health and Medical Communications - December 1, 2020 Category: Information Technology Authors: Srivastava, Anand Kumar Kumar, Yugal Singh, Pradeep Kumar Tags: Health Information Systems Medicine & Healthcare Source Type: research

SLAMMP Framework for Cloud Resource Management and Its Impact on Healthcare Computational Techniques
Technology such as cloud computing(CC) is constantly evolving and being adopted by the industries to manage their data and tasks. CC provides the resources for managing the tasks of the cloud users. The acceptance of the CC in healthcare industries is proven to be more cost-effective and convenient. CC manager has to manage the resources to provide services to the end-users of the healthcare sector. The SLAMMP framework discussed here shows how the resources are managed by using the concept of reinforcement learning (RL) and LSTM (long short-term memory) for monitoring and prediction of the cloud resources for healthcare o...
Source: International Journal of E-Health and Medical Communications - December 1, 2020 Category: Information Technology Authors: Prasad, Vivek Kumar Bhavsar, Madhuri D. Tags: Health Information Systems Medicine & Healthcare Source Type: research

fMRI Feature Extraction Model for ADHD Classification Using Convolutional Neural Network
This study addresses ADHD identification using functional magnetic resonance imaging (fMRI) data for the resting state brain by evaluating multiple feature extraction methods. The features of seed-based correlation (SBC), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) are comparatively applied to obtain the specificity and sensitivity. This helps to determine the best features for ADHD classification using convolutional neural networks (CNN). The methodology using fALFF and ReHo resulted in an accuracy of 67%, while SBC gained an accuracy between 84% and 86% and sensitivity betwe...
Source: International Journal of E-Health and Medical Communications - November 4, 2020 Category: Information Technology Authors: De Silva, Senuri Dayarathna, Sanuwani Udara Ariyarathne, Gangani Meedeniya, Dulani Jayarathna, Sampath Tags: Health Information Systems Medicine & Healthcare Source Type: research