Predictive Models of HIV/AIDS Epidemic Status using Data Mining Techniques: A Review

EasyChair Preprint 2279

Abstract

Data Mining plays an important role for uncovering new trends in health care organization which in turn helpful for all the parties associated with this field. Data mining is important for the health care sector in identification and detection of diseases, help researchers to make effective health care policies, develop recommendation systems and health profiles for patients. There are difficulties in evaluating the large data generated in the health care sector that are used to discover knowledge and find patterns for decision making. Health care data needs to be analyzed accurately in diagnosis, management and treatment of diseases. In this paper, we reviewed data mining techniques, its processes, tools, related works in HIV/AIDS and health care system. The purpose of this paper is to provide an insight towards requirements of health domain and about suitable choice of available technique and to understand about data mining and its importance in health care organizations.

Keyphrases: Classification, neural_networks, prediction

@booklet{EasyChair:2279,
  author    = {Daniel Mesafint and D.H. Manjaiah},
  title     = {Predictive Models of HIV/AIDS Epidemic Status using Data Mining Techniques: A Review},
  howpublished = {EasyChair Preprint 2279},
  year      = {EasyChair, 2019}}