Analyzing Health Data by Automatic Prediction of Patient Health Condition - Prajakta Sanap, Miss.; Santosh Kumar, Prof. (International Journal of Engineering and Technology, 2018)
The amount of data generated in various ï¬elds is increasing at high speed. Due to increase in the data generation, the problem regarding data storage arises. The increasing digitization in various sector has given rise to digitized data. The data in digital format is very convenient. The healthcare sector also has emerged with such convenient digital data. Digitization of healthcare information is useful for all healthcare stakeholders. The healthcare data once saved in digital format, it will be preserved for long time and also will be available anytime when needed. The health sector includes various different type of data and such varied type of digital data needs to be stored properly. The health digital data can be easily managed and processed by using Big Data concept. Most of the deaths are due to delayed disease detection and its treatment. If the disease is predicted earlier then proper treatment can be given on time to cure that disease. If the automatic disease prediction system is developed then disease can automatically be detected based on the symptoms observed in patient. The proposed system mainly focuses on Automatic prediction of disease. In this paper we use Classiï¬cation algorithms to classify various disease symptom. We have executed our technique and assessed its execution utilizing different dataset. The results of the experiment shows that this research gives more accuracy of predicted disease.Â Â