Colon Cancer Tissue Classification Using ML

Ashish Tripathi*, Kuldeep Kumar, Anuradha Misra, Brijesh Kumar Chaurasia

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

5 Citations (Scopus)

Abstract

In this paper, the classification of colon cancer tissues by means of machine learning approaches is evaluated. In today's world, a revolutionary advancement has come in the classification and diagnosis of diseases in the medical and healthcare sectors. Deep learning classifiers and machine learning methods are now broadly applied to accurately diagnose a number of diseases. Cancer is one of the world's most significant roots of death, appealing to the lives of one person out of every six. As per the national library of medicine, the third leading cause of death worldwide is colorectal cancer. Identifying an illness at a premature stage increases the chances of survival. Automated diagnosis and the classification of tissues from images can be completed much more quickly with the use of artificial intelligence. A publicly available IoT dataset CRC-VAL-HE-7K consisting of 7180 images, distributed among nine types of colorectal tissues: background, lymphocytes, adipose, mucus, colorectal adenocarcinoma epithelium, normal colon mucosa, debris, cancer-associated stroma, and, smooth muscle is used after preprocessing. Feature extraction is done by applying Differential-Box-Count on all blocks of images. The dataset is evaluated by these Machine Learning (ML) procedures: K-Nearest Neighbor, Support Vector Machine, Decision Tree, Random Forest, Extreme Gradient Boosting, and Gaussian Naive Bayes. Results show that the performance of Extreme Gradient Boosting is the best and most viable approach. .

Original languageEnglish
Title of host publication2023 6th International Conference on Information Systems and Computer Networks (ISCON)
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-6
Number of pages6
ISBN (Electronic)9798350346961
ISBN (Print)979-8-3503-4697-8
DOIs
Publication statusPublished - 2023
Event6th International Conference on Information Systems and Computer Networks, ISCON 2023 - GLA University, Mathura, India
Duration: 3 Mar 20234 Mar 2023
https://www.aconf.org/conf_186065

Publication series

Name2023 6th International Conference on Information Systems and Computer Networks, ISCON 2023

Conference

Conference6th International Conference on Information Systems and Computer Networks, ISCON 2023
Country/TerritoryIndia
CityMathura
Period3/03/234/03/23
Internet address

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