Big Data Analytics in HIV/AIDS Research
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Big Data Analytics in HIV/AIDS Research

Indexed In: SCOPUS View 2 More Indices
Release Date: April, 2018|Copyright: © 2018 |Pages: 294
DOI: 10.4018/978-1-5225-3203-3
ISBN13: 9781522532033|ISBN10: 152253203X|EISBN13: 9781522532040
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Description & Coverage
Description:

With the advent of new technologies in big data science, the study of medical problems has made significant progress. Connecting medical studies and computational methods is crucial for the advancement of the medical industry.

Big Data Analytics in HIV/AIDS Research provides emerging research on the development and implementation of computational techniques in big data analysis for biological and medical practices. While highlighting topics such as deep learning, management software, and molecular modeling, this publication explores the various applications of data analysis in clinical decision making. This book is a vital resource for medical practitioners, nurses, scientists, researchers, and students seeking current research on the connections between data analytics in the field of medicine.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Computational Analysis
  • Data Security and Privacy
  • Decision Support
  • Deep Learning
  • Infectious Disease
  • Management Software
  • Model Evaluation
  • Molecular Modeling
  • Prediction Techniques
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Editor/Author Biographies
Ali Al Mazari is an Australian Jordanian Scientist, with more than 18 years of Teaching, Training, Research and Consultation experience in Information & Communication Technologies (ICT) applied sciences and multidisciplinary domains, as well as Business Leadership and Management. Dr. Al Mazari earned his PhD in Science from the School of Information Technologies, Sydney University in Australia, early 2007, Master of Computing (Major in IT) from the School of Computing, Western Sydney University, Australia, 2001, Master of Leadership & Management in Education, Newcastle University, Australia, 2010, and received his Bachelor of Science in Mathematics and Computer Science, Jordan, 1994. Dr. Al Mazari was working as a Post-Doctoral Biomedical Informatics Researcher, at the School of Information Technologies, the University of Sydney, on investigating research issues in Bioinformatics and Biomedical Informatics (2007 to 2009). Dr. Al Mazari research activities were also taken place at the National ICT Australia (Centre of Excellence) (NICTA), produced Technical Reports and Research Seminars with audiences from many disciplines including ICT, bioinformatics, biostatistics, clinical immunology, molecular biology and machine learning (2006 to 2009). Dr. Al Mazari’s science-oriented research experience and interests are in the areas of computational biology, Bioinformatics, life sciences and the development of algorithms and models for biomedical applications and problems, and in the area of Information Security and Cybercrime. Dr. Al Mazari’s doctorate research focused on the application of computational methods for the analysis of HIV drug resistance dynamics. His contributions focus on developing algorithms, models, data mining and machine learning tools for the understanding of HIV/AIDS evolutionary behaviours and enabling further insights into understanding the trends of immunological and virological changes with reference to HIV viral evolution and behaviour.
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