Review on the Application of Machine Learning to Cancer Research

Article ID

CSTSDEQU71V

Advanced research on machine learning algorithms for cancer diagnosis and prediction accuracy.

Review on the Application of Machine Learning to Cancer Research

Henry Chibudike
Henry Chibudike
DOI

Abstract

This study reviews the application of machine learning through different algorithms in cancer research. In recent years, the introduction of machine learning has been an exciting tool that enhances cancer research which has improved statistical method of speeding up both fundamental and applied research considerably. The application of machine learning goes around in predicting the future events and outcomes with the available datasets. There is an indication that on yearly bases up to 14 million new cancer patients are diagnosed by Pathologists round the world, and they are people whose conditions are uncertain. Definitely, the diagnoses and prognoses of cancer have been performed by Pathologists. The research on machine learning flourished in 1980s and 1990s and information become digitalized through improved artificial network connectivity and computational power.

Review on the Application of Machine Learning to Cancer Research

This study reviews the application of machine learning through different algorithms in cancer research. In recent years, the introduction of machine learning has been an exciting tool that enhances cancer research which has improved statistical method of speeding up both fundamental and applied research considerably. The application of machine learning goes around in predicting the future events and outcomes with the available datasets. There is an indication that on yearly bases up to 14 million new cancer patients are diagnosed by Pathologists round the world, and they are people whose conditions are uncertain. Definitely, the diagnoses and prognoses of cancer have been performed by Pathologists. The research on machine learning flourished in 1980s and 1990s and information become digitalized through improved artificial network connectivity and computational power.

Henry Chibudike
Henry Chibudike

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Henry Chibudike. 2026. “. Global Journal of Computer Science and Technology – C: Software & Data Engineering GJCST-C Volume 22 (GJCST Volume 22 Issue C1): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Issue Cover
GJCST Volume 22 Issue C1
Pg. 39- 47
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GJCST-C Classification: F.1.1
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Review on the Application of Machine Learning to Cancer Research

Henry Chibudike
Henry Chibudike

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