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Big data analytics in HIV/AIDS research / Ali Al Mazari, editor. — 1 online resource. — (Advances in healthcare information systems and administration (AHISA) book series). — <URL:http://elib.fa.ru/ebsco/1741757.pdf>.

Record create date: 3/29/2018

Subject: AIDS (Disease); Data sets.; Data mining.; Datasets as Topic; HIV Infections — epidemiology; Data Mining; Acquired Immunodeficiency Syndrome; Sida.; Jeux de données.; Exploration de données (Informatique); MEDICAL — Forensic Medicine.; MEDICAL — Preventive Medicine.; MEDICAL — Public Health.; AIDS (Disease)

Collections: EBSCO

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Table of Contents

  • Title Page
  • Copyright Page
  • Book Series
  • Dedication
  • Editorial Advisory Board and List of Reviewers
  • Table of Contents
  • Detailed Table of Contents
  • Foreword
  • Preface
  • Acknowledgment
  • Introduction
  • Chapter 1: Computational Analysis of Reverse Transcriptase Resistance to Inhibitors in HIV-1
  • Chapter 2: Statistical and Computational Needs for Big Data Challenges
  • Chapter 3: Usage of Big Data Prediction Techniques for Predictive Analysis in HIV/AIDS
  • Chapter 4: Computational and Data Mining Perspectives on HIV/AIDS in Big Data Era
  • Chapter 5: Risks, Security, and Privacy for HIV/AIDS Data
  • Chapter 6: Prevalence in MSM Is Enhanced by Role Versatility
  • Chapter 7: Dissection of HIV-1 Protease Subtype B Inhibitors Resistance Through Molecular Modeling Approaches
  • Chapter 8: HIV-Associated Neurocognitive Disorder
  • Related References
  • Compilation of References
  • About the Contributors
  • Index

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