Open AccessPerformance Analysis of Algorithms on Different Types of Health Related Datasets
Author(s) -
Nazmun Nahar Khanom,
Fatema Nihar,
Syed Sahariar Hassan,
Linta Islam
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1577/1/012051
Subject(s) - computer science , health care , data mining , order (exchange) , machine learning , data science , algorithm , artificial intelligence , economics , finance , economic growth
Healthcare related data are very important for people of the global community to make them aware of their lives and rights. By analyzing performances of different types of health-related data produce efficient valuable rich information; which can be used in further healthcare research. From the previous works we have seen, they have also tried to analyze the performances of algorithms to modify the accuracy but this study is unique as it has used lots of different types of health-related datasets and algorithms together to achieve better accuracy. This study aims to analyze performances of algorithms on different types of healthcare related data to produce effective information in order to assist global community in their daily life. This will help people to lead a healthy and comfortable life and innovate new ideas to further change their lifestyle. The effective information or the standard used here is the accuracy of the applied algorithms.