Scopus Indexed Publications

Paper Details


Title
A study on dengue fever in bangladesh: Predicting the probability of dengue infection with external behavior with machine learning
Author
Md. Sanzidul Islam, AKM Shahariar Azad Rabby, Sharun Akter Khushbu, Touhid Bhuiyan,
Email
Abstract
The “2019 Dengue Outbreak” was a nationwide pandemic situation in Bangladesh, particularly in Dhaka city. About 179 people died and 101,354 confirmed dengue cases were found all over the country. The developing countries like Bangladesh have some limitations in the medical sector and many people don't get proper treatment in time. Henceforth, this research work has attempted to predict the chances to get infected with dengue fever from some external behaviors, like-fever, pain, sitophobia, headache etc. This article has demonstrated a model to predict the probability of dengue fever before taking the pathological test. So, the suspective patient may get some initial diagnosis by giving their anatomical symptoms as input and further this will decrease the dependency on the pathological test for acquiring the primary treatment. Different machine learning models are used to predict the probability and an accuracy near to 100% has been achieved finally.

Keywords
Machine Learning model , Dengue disease , anatomical symptoms
Journal or Conference Name
5th International Conference on Intelligent Computing and Control Systems (ICICCS)
Publication Year
2021
Indexing
scopus