Article Info

Published 19 Sep 2025

Volume / Issue 1 / Issue 5

Pages 107–111

DOI

10.64823/ijter.2505009

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Open Access Research Article

5 pages PDF

Intelligent Prediction of Cancer Diseases through Machine Learning

by ,

International Journal of Technology and Emerging Research 2025 , 1 (5) , 107–111

10.64823/ijter.2505009

Received: 17 Sep 2025 Published: 19 Sep 2025

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Cite this article

APA

Veeramuthu P, & Rajesh D (2025). Intelligent Prediction of Cancer Diseases through Machine Learning. International Journal of Technology and Emerging Research, 1(5): 107–111. https://doi.org/10.64823/ijter.2505009

MLA

Veeramuthu P, et al. "Intelligent Prediction of Cancer Diseases through Machine Learning." International Journal of Technology and Emerging Research, vol. 1, no. 5, 2025, pp. 107–111. https://doi.org/10.64823/ijter.2505009

Chicago

Veeramuthu P, Rajesh D. "Intelligent Prediction of Cancer Diseases through Machine Learning." International Journal of Technology and Emerging Research 1, no. 5 (2025): 107–111. https://doi.org/10.64823/ijter.2505009

BibTeX

@article{Veeramuthu P2025intelligent, author = {Veeramuthu P and Rajesh D}, title = {Intelligent Prediction of Cancer Diseases through Machine Learning}, journal = {International Journal of Technology and Emerging Research}, year = {2025}, volume = {1}, number = {5}, pages = {107–111}, doi = {10.64823/ijter.2505009}, }

Abstract

Cancer remains one of the leading causes of mortality worldwide, and timely diagnosis plays a critical role in improving patient survival rates. Traditional diagnostic methods often face challenges such as complexity, cost, and human error, necessitating the development of intelligent computational systems. This study proposes a machine learning–based framework for the intelligent prediction of cancer diseases, aiming to improve accuracy, reduce misdiagnosis, and support clinical decision-making. The proposed approach integrates feature selection, optimized model training, and performance evaluation to construct a scalable predictive model applicable to various types of cancer.

Keywords: machine learning, Cancer Prediction, Intelligent Systems, Early Diagnosis, Clinical Decision Support

© 2025 The Author(s). Published by IORO Publications. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original author and source are credited, a link to the license is provided, and any changes are indicated.