A systematic literature review of cloud computing in eHealth

Cloud computing in eHealth is an emerging area for only few years. There needs to identify the state of the art and pinpoint challenges and possible directions for researchers and applications developers. Based on this need, we have conducted a systematic review of cloud computing in eHealth. We searched ACM Digital Library, IEEE Xplore, Inspec, ISI Web of Science and Springer as well as relevant open-access journals for relevant articles. A total of 237 studies were first searched, of which 44 papers met the Include Criteria. The studies identified three types of studied areas about cloud computing in eHealth, namely (1) cloud-based eHealth framework design (n=13); (2) applications of cloud computing (n=17); and (3) security or privacy control mechanisms of healthcare data in the cloud (n=14). Most of the studies in the review were about designs and concept-proof. Only very few studies have evaluated their research in the real world, which may indicate that the application of cloud computing in eHealth is still very immature. However, our presented review could pinpoint that a hybrid cloud platform with mixed access control and security protection mechanisms will be a main research area for developing citizen centred home-based healthcare applications

In search for a viable pedagogical agent in assistive applications for dyslexic children

TO attend to dyslexia, many studies have been conducted, and in the frontline is the design of assistive applications for dyslexic children. However, studies have not been focused on the nature and appearance of these pedagogical agents used in assistive applications, especially considering children’s preferences and their users’ experiences.Hence, this study employs Systematic Literature Review (SLR) methodology to collate and analyse the research-based and publicly-available assistive applications designed for dyslexic children.The findings present two categories of virtual assistants used in the analysed assistive applications, which are girl-like and animal-like objects.This girl-like object is used by 83.3% of the analysed works. We then proceed with and on-site experiment to collect the dyslexic children’s preferences.The result showed that boy-like objects are much more preferable, depending on their gender, which contradicts with previous works that present girl-like objects as avatar most of the time

An innovative IoT service for medical diagnosis

Due to the misdiagnose of diseases that increased recently in a scarily manner, many researchers devoted their efforts and deployed technologies to improve the medical diagnosis process and reducing the resulted risk. Accordingly, this paper proposed architecture of a cyber-medicine service for medical diagnosis, based internet of things (IoT) and cloud infrastructure (IaaS). This service offers a shared environment for medical data, and extracted knowledge and findings between patients and doctors in an interactive, secured, elastic and reliable way. It predicts the medical diagnosis and provides an appropriate treatment for the given symptoms and medical conditions based on multiple classifiers to assure high accuracy. Moreover, it entails different functionalities such as on-demand searching for scientific papers and diseases description for unrecognized combination of symptoms using web crawler to enrich the results. Where such searching results from crawler, are processed, analyzed and added to the resident knowledge base (KB) to achieve adaptability and subsidize the service predictive ability

Deep Learning-aided Brain Tumor Detection: An Initial ‎Experience based Cloud Framework ‎

Lately, the uncertainty of diagnosing diseases increased and spread due to the huge intertwined and ambiguity of symptoms, that leads to overwhelming and hindering the reliability of the diagnosis ‎process. Since tumor detection from ‎MRI scans depends mainly on the specialist experience, ‎misdetection will result an inaccurate curing that might cause ‎critical harm consequent results. In this paper, detection service for brain tumors is introduced as ‎an aiding function for both patients and specialist. The ‎paper focuses on automatic MRI brain tumor detection under a cloud based framework for multi-medical diagnosed services. The proposed CNN-aided deep architecture contains two phases: the features extraction phase followed by a detection phase. The contour ‎detection and binary segmentation were applied to extract the region ‎of interest and reduce the unnecessary information before injecting the data into the model for training. The brain tumor ‎data was obtained from Kaggle datasets, it contains 2062 cases, ‎‎1083 tumorous and 979 non-tumorous after preprocessing and ‎augmentation phases. The training and validation phases have been ‎done using different images’ sizes varied between (16, 16) to ‎‎ (128,128). The experimental results show 97.3% for detection ‎accuracy, 96.9% for Sensitivity, and 96.1% specificity. Moreover, ‎using small filters with such type of images ensures better and faster ‎performance with more deep learning.

DiaMe: IoMT deep predictive model based on threshold aware region growing technique

Medical images magnetic resonance imaging (MRI) analysis is a very challenging domain especially in the segmentation process for predicting tumefactions with high accuracy. Although deep learning techniques achieve remarkable success in classification and segmentation phases, it remains a rich area to investigate, due to the variance of tumefactions sizes, locations and shapes. Moreover, the high fusion between tumors and their anatomical appearance causes an imprecise detection for tumor boundaries. So, using hybrid segmentation technique will strengthen the reliability and generality of the diagnostic model. This paper presents an automated hybrid segmentation approach combined with convolution neural network (CNN) model for brain tumor detection and prediction, as one of many offered functions by the previously introduced IoMT medical service “DiaMe”. The developed model aims to improve extracting region of interest (ROI), especially with the variation sizes of tumor and its locations; and hence improve the overall performance of detecting the tumor. The MRI brain tumor dataset obtained from Kaggle, where all needed augmentation, edge detection, contouring and binarization are presented. The results showed 97.32% accuracy for detection, 96.5% Sensitivity, and 94.8% for specificity

Evaluasi penerapan konsep integrasi data menggunakan dhis2 di kementerian kesehatan

Latar Belakang: Undang-Undang Nomor 36 Tahun 2009 tentang Kesehatan Pasal 168, untuk menyelenggarakan upaya kesehatan yang efektif dan efisien diperlukan informasi kesehatan. Informasi yang berkualitas diperoleh dari pengumpulan data yang baik sehingga menjadi acuan dalam proses manajemen, perencanaan dan pengambilan keputusan. Namun hingga saat ini, SIK yang ada belum mampu menyediakan data dan informasi yang cepat, akurat dan tepat waktu dikarenakan masih adanya fragmentasi sistem informasi, lemahnya manajemen data dan sistem pendukung pengambilan keputusan. Berdasarkan hal tersebut, sejak tahun 2106 Kementerian Kesehatan mengadopsi aplikasi DHIS2 sebagai data repository yang bertujuan mengintegrasikan data, menguatkan proses manajemen data dan bahan pengambilan keputusan di Kementerian Kesehatan.Tujuan: Mendeskripsikan input, proses dan output dalam pelaksanaan integrasi data serta monitoring dan evaluasi pelaksanaan integrasi data menggunakan DHIS2 di Kementerian Kesehatan sesuai dengan kerangka kerja integrated data repository dari WHO. Metode Penelitian: Deskriptif kualitatif dengan rancangan studi kasus. Data dikumpulkan dengan cara observasi, telaah dokumen dan wawancara mendalam dengan pejabat struktural, staf teknis dan konsultan di Pusdatin Kementerian KesehatanMetode : Deskriptif kualitatif dengan rancangan studi kasus pada penerapan konsep integrasi data berdasarkan kerangka integrated data repository dari WHO.Hasil : Implementasi DHIS2 di Kementerian Kesehatan menggunakan infrastruktur server terpusat yang mendukung kemampuan cloud system. Aplikasi DHIS2 digunakan sebagai alat untuk mengumpulkan data agregate dari berbagai sumber dan menyajikannya dalam tampilan dashboard.  Kebijakan tertulis tentang integrasi data belum ada, saat integrasi disusun hanya berdasarkan kesepakatan antar unit. Regulasi tentang standar pelaksanaan integrasi belum ada, standar kode puskesmas digunakan sebagai standar integrasi data yang bersumber dari puskesmas. Sumber data yang telah diintegrasikan bersumber dari sumber data rutin yaitu aplikasi SIHA, SITT, Keluarga Sehat dan Komdat sedangkan sumber data rutin lainnya dan sumber data non rutin belum diintegrasikan ke DHIS2. Proses pencocokan data antara dashboard DHIS2 dengan sumber data pada aplikasi komdat diperoleh hasil yang sama pada data bulanan dan triwulan sedangkan pada data tahunan masih ditemukan perbedaan.Kesimpulan: Integrasi data menggunakan DHIS2 belum mampu menghasilkan data dan informasi berkualitas yang berasal dari berbagai sumber data sehingga saat ini belum dapat digunakan untuk memperkuat proses manajemen data dan bahan pembuatan kebijakan

Integrated, reliable and cloud-based personal health record: a scoping review.

Personal Health Records (PHR) emerge as an alternative to integrate patient’s health information to give a global view of patients' status. However, integration is not a trivial feature when dealing with a variety electronic health systems from healthcare centers. Access to PHR sensitive information must comply with privacy policies defined by the patient. Architecture PHR design should be in accordance to these, and take advantage of nowadays technology. Cloud computing is a current technology that provides scalability, ubiquity, and elasticity features. This paper presents a scoping review related to PHR systems that achieve three characteristics: integrated, reliable and cloud-based. We found 101 articles that addressed thosecharacteristics. We identified four main research topics: proposal/developed systems, PHR recommendations for development, system integration and standards, and security and privacy. Integration is tackled with HL7 CDA standard. Information reliability is based in ABE security-privacy mechanism. Cloud-based technology access is achieved via SOA.CONACYT - Consejo Nacional de Ciencia y TecnologíaPROCIENCI

On-Cloud Motherhood Clinic: A Healthcare Management Solution for Rural Communities in Developing Countries

Background: Modern telecommunication infrastructure enables bridging of the digital divide between rural and urban healthcare services, promoting the provision of suitable medical care and support. Thus far, there has been some positive impacts to applying mobile health (m-Health) solutions, but their full potential in relation to cloud computing has is yet to be realised. It is imperative to develop an innovative approach for addressing the digital divide in a context of developing country. Method: Adopting a design science research approach (DSR), this study describes an innovative m-Health solution utilising cloud computing that enables healthcare professionals and women in rural areas to achieve comprehensive maternal healthcare support. We developed the solution framework through iterative prototyping with stakeholders’ participation, and evaluated the design using focus groups. Results: The cloud-based solution was positively evaluated as supporting healthcare professionals and service providers. It was perceived to help provide a virtual presence for evaluating and diagnosing expectant mothers’ critical healthcare data, medical history, and in providing necessary service support in a virtual clinic environment. Conclusions: The new application offers benefits to target stakeholders enabling a new practice-based paradigm applicable in other healthcare management. We demonstrated utilities to address target problems as well as the mechanism propositions for meeting the information exchange demand for better realisation of practical needs of the end users. Available at: https://aisel.aisnet.org/pajais/vol12/iss1/3

Abordagens sobre computação na nuvem: uma breve revisão sobre segurança e privacidade aplicada a e-saúde no contexto do Programa Conecte SUS e Rede Nacional de Dados em Saúde (RNDS) / Approaches to cloud computing: a brief review of security and privacy applied to e-health in the context of the Connect SUS Program and the National Health Data Network (RNDS)

 No presente artigo, apresentamos uma breve revisão da literatura para e-saúde em ambiente de armazenamento na nuvem. Foram selecionados artigos nas fontes da Medline e Google Scholar, objetivando encontrar informações recentes sobre esta tecnologia emergente para os serviços de saúde. Com relevância à segurança e privacidade de dados em diferentes estudos de computação em nuvem abordaram este tema. Armazenar informações como prontuários eletrônicos e dados relacionados à saúde na nuvem, requerer precauções para garantir a segurança e confidencialidade. Os provedores deste serviço devem garantir que os mecanismos de segurança estejam em vigor para evitar acesso não autorizado e violações de dados. O conhecimento na área de e-saúde e do Programa Conecte SUS também são abordados na sua essência quanto as necessidades de tratamentos na proteção dos dados. A LGPD é apresentada como um marco inovador na questão da conduta e cuidados que as empresas, profissionais e usuários devem ter na utilização dos sistemas e aplicativos em nuvem. Ademais, tópicos importantes da Rede Nacional de Dados em Saúde, ressaltam que os pacientes devem ser mantidos informados sobre como seus dados de saúde devem ser armazenados e gerenciados. O bom senso, o consentimento, a análise da importância na manutenção de dados específicos relativizados à proteção das informações e penalidades impostas no caso de uso indevido são aqui analisadas

The impact of technological innovation on marketing: individuals, organizations and environment: a systematic review

Marketing is the cornerstone of an organization as it is vital to both strategic planning and business operations. An organization’s longrun success depends on its ability to create value for its customers, and marketing plays a crucial role in achieving this goal. This review paper attempts to broaden the body of knowledge concerning the impact of technological innovation on the marketing sector by presenting a systematic review along with a set of paths for future research. A total of 93 articles from 716 articles were systematically selected from different academic journals between 1999 and 2019. The articles were reviewed and summarized according to the individual, organizational, and environmental impact of technological innovation on the marketing sector. The study elaborates on different applications of advanced technologies and their impact on the marketing sector. This will help in conceptualizing the impact of technological innovation on the marketing sector in future studie