Deep learning techniques for biomedical and health informatics
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: Deep learning techniques for biomedical and health informatics
Deep learning techniques for biomedical and health informatics
Studies in Big Data 68Sujata Dash • Biswa Ranjan Acharya • Mamta Mittal • Ajith Abraham • Arpad Kelemen EditorsDeep Learning Techniques for Biomedical Deep learning techniques for biomedical and health informatics l and Health InformaticsỄỊ springerStudies in Big DataVol lime 68Series EditorJanusz Kacprzyk, Polish Academy of Sciences. Warsaw. PolandThe scries “Studies in Big Data” (SBD) publishes new developments and advances in the various areas of Big Data- quickly and with a high quality. The intent is to Deep learning techniques for biomedical and health informatics cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer science, physics, economicsDeep learning techniques for biomedical and health informatics
and life sciences. The books of the scries refer to the analysis and understanding of large, complex, and/or distributed data sets generated from receStudies in Big Data 68Sujata Dash • Biswa Ranjan Acharya • Mamta Mittal • Ajith Abraham • Arpad Kelemen EditorsDeep Learning Techniques for Biomedical Deep learning techniques for biomedical and health informatics tions, such as emails or video click streams and other. The series contains monographs, lecture notes and edited volumes in Big Data spanning the areas of computational intelligence including neural networks, evolutionary computation, soft computing, fuzzy systems, as well as artificial intelligence Deep learning techniques for biomedical and health informatics , data mining, modern statistics and Operations research, as well as self-organizing systems. Of particular value to both the contributors and the reaDeep learning techniques for biomedical and health informatics
dership arc the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.** IndeStudies in Big Data 68Sujata Dash • Biswa Ranjan Acharya • Mamta Mittal • Ajith Abraham • Arpad Kelemen EditorsDeep Learning Techniques for Biomedical Deep learning techniques for biomedical and health informatics s, Zcntralblatt Math: MctaPrcss and springcrlink.More information about this scries at http://www.springer.eom/scries/l 1970Sujata Dash • Biswa Ranjan Acharya •Mamta Mittal • Ajith Abraham •Arpad KelemenEditorsDeep Learning Techniques for Biomedical and Health InformaticsSpringerEditorsSujata DashDe Deep learning techniques for biomedical and health informatics partment of Computer ScienceNorth Orissa UniversityTakatpur, Odisha, IndiaManna MittalComputer Science and EngineeringDepartmentG. B. Pant GovernmentDeep learning techniques for biomedical and health informatics
Engineering CollegeNew Delhi, Delhi, IndiaArpad KeiemenDepartment of Organizational Systemsand Adult HealthUniversity of MarylandBaltimore, MD, USABisStudies in Big Data 68Sujata Dash • Biswa Ranjan Acharya • Mamta Mittal • Ajith Abraham • Arpad Kelemen EditorsDeep Learning Techniques for BiomedicalStudies in Big Data 68Sujata Dash • Biswa Ranjan Acharya • Mamta Mittal • Ajith Abraham • Arpad Kelemen EditorsDeep Learning Techniques for BiomedicalGọi ngay
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