International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 6 Issue 6
November-December 2024

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

A SMOTE Boosting Based Blood Cancer Prediction Using Leukemia Microarray Dataset

Author(s) M.V.PHANINDRA, Dr. G. THIPPANNA
Country India
Abstract Leukemia is a type of blood cancer primarily involving abnormal white blood cell production. This condition leads to an irregular increase in white blood cells compared to normal levels. Despite advancements, accurately classifying cancers using microarray data remains challenging. Many data mining techniques have struggled due to limited sample sizes, posing significant challenges for organizations. While frequently used in cancer diagnosis, these methods often fall short in delivering improved results. This research introduces an innovative approach utilizing ensemble learning algorithm to analyze microarray data from leukemia cells, aiming to predict early-stage leukemia. SMOTE (Synthetic Minority Over-sampling Technique) boosting is an advanced technique used to address class imbalance in predictive modeling, particularly in the context of medical data. SMOTE works by generating synthetic samples of the minority class by interpolating between existing instances. The integration of AdaBoost, SMOTE enhanced the model’s ability to focus on misclassified instances, thus improving the overall prediction accuracy.
Keywords SMOTE. Machine Learning, Blood Cancer, Leukemia Microarray
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-12-14
Cite This A SMOTE Boosting Based Blood Cancer Prediction Using Leukemia Microarray Dataset - M.V.PHANINDRA, Dr. G. THIPPANNA - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.33088
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.33088
Short DOI https://doi.org/g8wkj3
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 6 Isu 6Cover Page Vol 6 Isu 5Cover Page Vol 6 Isu 4

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9898-5948-55 editor@ijfmr.com