Personal Medical Data Analysis
Monograph
(Sprache: Englisch)
Monograph considers a problem of analysis of personal medical data and describes the application of machine learning technology and Big data to solve the problem of personalized approach in the tasks of making medical decisions. This information to develop...
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Monograph considers a problem of analysis of personal medical data and describes the application of machine learning technology and Big data to solve the problem of personalized approach in the tasks of making medical decisions. This information to develop innovative approaches to risk forecasting, modeling therapies, and improving the quality of medical care by personalizing treatment schemes of patients is used. And it will also allow you to effectively optimize data processing even when new information revenues come from different sources. Also this monograph describes the verifying methods of medical specialty from user profile of online community for health-related advices, actual fuzzy logic approach for modelling the behavior classification of social news aggregations users and the analysis of personal patient information whisch is one of critical factors for analysis of medical data. In medical and biological research, as well as in practical medicine, the range of tasks to be solved is so wide that it is possible to use any of the methodologies of machine learning and Big Data.
Autoren-Porträt von Solomiia Fedushko, Natalia Shakhovska, Nataliia Melnykova
Fedushko, SolomiiaFedushko S. PhD, As. Prof. at SCIA Department, Lviv Polytechnic National University (LPNU).Shakhovska N. Sc.D., Prof., Head at AIS Department, LPNU.Melnykova N. PhD, As. Prof. at AIS Department, LPNU.Melnykov V. PhD, As. Prof. at GS Department, D. Galytsky Lviv National Medical University.Syerov Yu. PhD, As. Prof. at the SCIA Department, LPNP.
Bibliographische Angaben
- Autoren: Solomiia Fedushko , Natalia Shakhovska , Nataliia Melnykova
- 2019, 112 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6139447992
- ISBN-13: 9786139447992
Sprache:
Englisch
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