EventsMOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed.
Published
This submission belongs to the session 05. USEDAT.NET: USA-Europe Data Analysis Trends & Complex Networks Mini Congress Series, Coruña, SP-Miami, USA, 2023 of the event MOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed.
Published date
10 May, 2023
Academic Editor
author-avatarMOL2NET team
Citation
Aliya Batool, Importance of Machine Learning in Cancer Classification Using Digital Image Dataset, in Proceedings of MOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed., 25 December–31 December 2023, MDPI: Basel, Switzerland
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Importance of Machine Learning in Cancer Classification Using Digital Image Dataset

1. Department of Information Technology, The Islamia University Bahawalpur, Pakistan
Abstract

A research initiative that attempts to categorize the many forms of cancer using machine learning algorithms. Machine learning strategies are being researched to enhance the precision and speed with which cancer is diagnosed. The researchers compiled a dataset consisting of cancer patients. They used several machine learning algorithms to analyze the data to identify patterns and characteristics that may be used to differentiate between the various forms of cancer. According to the research findings, the machine learning algorithms were practical in correctly categorizing the multiple forms of cancer, and the accuracy of the models was greater than that of conventional diagnosis techniques. The research results indicate that machine learning algorithms can be a valuable cancer detection tool. These algorithms have the potential to assist in improving patient outcomes by more rapidly and correctly detecting the proper diagnosis.

Keywords
Machine Learning
Classification
Digital Images
Cancer
Manuscript
Role of Image Processing in Medical Science
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