Estimating The Accuracy of Classifiers in Analyzing Multiple Diseases

Olusola Olajide Ajayi
Additional contact information
Olusola Olajide Ajayi: Department of Computer Science, Faculty of Science, Adekunle Ajasin University, Akungba-Akoko, Ondo, Nigeria

International Journal of Research and Innovation in Applied Science, 2022, vol. 7, issue 9, 92-96

Abstract: Medical data are regarded as been sensitive not only in terms of the need to keep it private but also and majorly in terms of the need to get it right and accurate. Patients’ medical data are diagnose and analyze with optimal accuracy to avoid error of prescription. Multiple diseases are one that can easily get complicated where the analysis of symptoms are not right. Machine learning is a known field of inquiry found very suitable in the medical area for analysis of medical diagnosis. The need for the right classification algorithm to deploy for a particular medical experimentation/prediction becomes very germane especially in the case of multiple diseases. No doubt, many researches have been done in this regard but not specifically tailored towards multiple diseases. The study which utilizes medical data from third party, www.kaggle.com, applied selected common three classification algorithms on the dataset. The result of the experimentation carried out using WEKA Explorer, shows Artificial Neural Network (ANN) outperforms Decision Tree and Naïve Bayes in terms of level of accuracy.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijrias/ ... -7-issue-9/92-96.pdf (application/pdf)
https://www.rsisinternational.org/virtual-library/ ... 051938702.1694191524 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjf:journl:v:7:y:2022:i:9:p:92-96

Access Statistics for this article

International Journal of Research and Innovation in Applied Science is currently edited by Dr. Renu Malsaria

More articles in International Journal of Research and Innovation in Applied Science from International Journal of Research and Innovation in Applied Science (IJRIAS)
Bibliographic data for series maintained by Dr. Renu Malsaria ().