It is a pleasure for me to invite you to participate to the Special
\nIssue on “Artificial Intelligence for Mobile Health Data Analysis and
\nProcessing”, Journal of Mobile Information Systems, Hindawi (Impact
\nFactor: 0.958)<\/p>\n
https:\/\/apps.clarivate.com\/jif\/home?journal=MOB%20INF%20SYST&year=2017&editions=SCIE&pssid=H1-bx2Fw5nVTKro6PIUp6Vx2FwVmcPzfUp6XsX2-18x2daTCY2r3thC9TPTpUU0DGKQx3Dx3DnQPUZ5ym7U9AXBYsV1z7uQx3Dx3D-9vvmzcndpRgQCGPd1c2qPQx3Dx3D-wx2BJQh9GKVmtdJw3700KssQx3Dx3D<\/a>.<\/p>\n You are welcome to distribute this call or to send us the names, e-mail We would appreciate a brief feedback about your interest at your We are looking forward to receiving your contribution, and we remain<\/p>\n Yours sincerely,<\/p>\n Giovanna Sannino,<\/p>\n Lead Guest Editor of the Special Issue on “Artificial Intelligence for =========================================================================== Mobile Information Systems<\/p>\n Impact Factor: 0.958 MISSION: Nowadays, Internet of Things (IoT) is changing eHealth and especially This special issue especially focuses on the feasibility of machine TOPICS: The topics for this special issue include but not limited to:<\/p>\n – Novel architectures for m-Health data analysis and processing PAPER SUBMISSION: Authors are invited to submit their papers written in English in pdf. IMPORTANT DATES: Submission deadline: August 03, 2018 (extended and firm)
\naddresses, and affiliations of colleagues that you would recommend
\nenriching the content of the theme issue.<\/p>\n
\nearliest convenience, and of course your contribution in due time.<\/p>\n
\nMobile Health Data Analysis and Processing”, JMIS, Hindawi.<\/p>\n
\nSpecial Issue on Artificial Intelligence for Mobile Health Data Analysis
\nand Processing<\/p>\n
\n===========================================================================<\/p>\n
\n——————————————————————————<\/p>\n
\nmobile Health (m-Health) systems. Currently, more and more fixed and
\nmobile medical devices installed in patients\u00e2\u20ac\u2122 personal body networks,
\nmedical devices and in surrounding clinical\/home environments collect
\nand send a huge amount of heterogeneous health data to healthcare
\ninformation systems for their analysis. In this context machine learning
\nand data mining techniques are becoming more and more important in many
\nreal-life problems. An important number of these techniques are
\ndedicated to health data processing and analysis on mobile devices.
\nSeveral mobile applications based on these techniques have emerged as an
\nessential technology for improving the quality of medical diagnosis and
\ntreatments of many illnesses as well as many health disorders.
\nExisting techniques used for processing health data can be broadly
\nclassified into two categories: (a) Non-Artificial Intelligence (AI)
\nsystems & (b) Artificial Intelligence systems. Even though non-AI
\ntechniques are less complex in nature, most of the systems suffer from
\nthe drawbacks of inaccuracy and lack of convergence. Hence, these
\nsystems are generally replaced by AI based systems which are much
\nsuperior to the conventional systems. AI techniques are mostly hybrid in
\nnature and include Artificial Neural Networks (ANN), Fuzzy theory,
\nEvolutionary algorithms, etc. Though most of the techniques are
\ntheoretically sound, the potential of these techniques is not fully
\nexplored for practical applications. Many of the computational
\napplications still depend on Non-AI systems, which limit their practical
\nusage.<\/p>\n
\nlearning and data mining techniques on practical mobile health
\napplications. These practical mobile applications include for instance
\nbiomedical, medical images processing, health management, etc. This
\nspecial issue serves for discovering the untold advantages of data
\nscience techniques for practical mobile health applications, and also
\nbrings out solutions for many real-life problems through advanced
\ntheoretical and experimental approaches.<\/p>\n
\n——————————————————————————<\/p>\n
\n– Fuzzy approaches for mobile applications dedicate to health management
\n– Evolutionary algorithms for optimization methodologies for mHealth
\napplications
\n– Medical-informatics applications using intelligence methodologies on
\nmobile devices
\n– Applications of AI techniques in signal & image processing on mobile
\ndevices
\n– Mobile bio-medical applications involving ANN, fuzzy theory, etc
\n– Data Mining for health data processing and analysis on mobile devices
\n– Machine Learning and Deep learning for health-related mobile applications<\/p>\n
\n——————————————————————————<\/p>\n
\nPlease, find information on how to prepare it at:
\nhttps:\/\/www.hindawi.com\/journals\/misy\/guidelines\/<\/a>.<\/p>\n
\n——————————————————————————<\/p>\n
\nPublication date: December, 2018<\/p>\n