An effective leukemia prediction technique using supervised machine learning classification algorithm

Mohammad Akter Hossain, Mubtasim Islam Sabik, Md Moshiur Rahman, Shadikun Nahar Sakiba, A. K.M. Muzahidul Islam, Swakkhar Shatabda, Salekul Islam, Ashir Ahmed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Leukemia is not only fatal in nature, the treatment is also extremely expensive. Leukemia’s second stage (typically there are four stages) is enough to blow a large hole in a family’s savings. In this paper, we have designed a supervised machine learning model that accurately predicts the possibility of Leukemia at an early stage. We mainly focus on regular symptoms and the probabilities of a subject to develop Leukemia later on. The parameters or features are usually information available at regular checkups. Firstly, we have defined 17 parameters in consultation with the specialist doctors and then we have collected primary data through surveys of different Leukemia and Non Leukemia patients from hospitals. We have divided the data into train and test datasets and applied different machine learning algorithms such as Decision Tree, Random Forest, KNN, Linear Regression, Adaboost, Naive Bayesian, etc. to find out the accuracy. We obtained 98% of accuracy using Decision Tree and Random Forest, 97.21% using KNN, 91.24% using Logistic Regression, 94.24% using Adaboost, and 75.03% using Naive Bayesian, respectively. It is observed that the Decision Tree and the Random Forest classifier outperform the rest.

Original languageEnglish
Title of host publicationProceedings of International Conference on Trends in Computational and Cognitive Engineering - Proceedings of TCCE 2020
EditorsM. Shamim Kaiser, Anirban Bandyopadhyay, Mufti Mahmud, Kanad Ray
PublisherSpringer Science and Business Media Deutschland GmbH
Pages219-229
Number of pages11
ISBN (Print)9789813346727
DOIs
Publication statusPublished - 2021
Event2nd International Conference on Trends in Computational and Cognitive Engineering, TCCE 2020 - Savar, Bangladesh
Duration: Dec 17 2020Dec 18 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1309
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference2nd International Conference on Trends in Computational and Cognitive Engineering, TCCE 2020
CountryBangladesh
CitySavar
Period12/17/2012/18/20

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

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