Health Care Data Analysis through Machine Learning Meta Heuristic Algorithm

C. Kalpana and Dr.B. Booba

The increasing volume of information is gathered in medical and healthcare systems. It is the convergences of different fields are important in medical and healthcare data analysis. This research is an innovative direction of precision and personalized medicine through metaheuristic or machine learning algorithm. The development brings a distinctive opportunity and good promising results to solve different critical tasks in healthcare research. A machine learning intelligence environment recommended decision makers information via various soft computing intelligent algorithms. Normally, the knowledge derived from information or data processing, through the mathematical models and algorithms. Previously numerous efforts have been implemented via various techniques such as optimization, mathematical modeling, statistical analysis, biomedical informatics, etc. This paper will extend along the lines of optimization methods and machine learning algorithm, and to build new models for solving or decision making in healthcare challenges. The main purpose of this article is to implement a new algorithm with the idea from the smelling sense of Bear, for the dynamic decision making system in the current healthcare research.

Volume 12 | Issue 7

Pages: 196-201

DOI: 10.5373/JARDCS/V12I7/20202000