Toward Automating HIV Identification: Machine Learning for Rapid Identification of HIV-Related Social Media Data.

Journal: Journal of acquired immune deficiency syndromes (1999)
PMID: 28079723

Abstract

INTRODUCTION: "Social big data" from technologies such as social media, wearable devices, and online searches continue to grow and can be used as tools for HIV research. Although researchers can uncover patterns and insights associated with HIV trends and transmission, the review process is time consuming and resource intensive. Machine learning methods derived from computer science might be used to assist HIV domain experts by learning how to rapidly and accurately identify patterns associated with HIV from a large set of social data.

Authors

  • Sean D Young
    *Department of Family Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA; †University of California Institute for Prediction Technology, University of California, Los Angeles, CA; and ‡Department of Computer Science, University of California, Los Angeles, CA.
  • Wenchao Yu
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.

Keywords

External Resources

Popular Topics
Recent Journals