Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Lung Cancer Detecting using Radiomics Features and Machine Learning Algorithm Subject The topic of the resource Feature Extraction; Image Classification; Lung Cancer; Machine Learning; Radiomics; Selection Description An account of the resource Lung Cancer Incidence across the globe is the second leading cancer type tallying to about 2,206,771 during 2020 and is estimated to rise to about 3,503,378 by 2040 for both male and female sexes and for all ages accounting to 11.4% as per Globocan 2020 [1]. It is the leading death-causing cancer. Lung Cancer [2] in broad terms encompasses Trachea, bronchus as well as lungs. Purpose: The study is aimed to understand Radiomics based approach in the identification as well as classification of CT Images with Lung Cancer when Machine Learning (ML) algorithms are applied. Method: CT Image from LIDC-IDRI [4] Dataset has been chosen. CT Image Dataset was balanced and image features by PyRadiomics library were collected. Various ML features classification algorithms are utilized to create models and matrices adopted in judging their accuracies. The models, distinctive capacity is assessed by receiver operating characteristics (ROC) analysis. Result: The Accuracy scores and ROC-AUC values obtained for various Classification Model are as follows, for Ada Boosting, the accuracy score was 0.9993 ROC-AUC was 0.9993 and followed by GBM, the accuracy score was 0.9993, was 0.9992. Conclusion: Extracting texture parameters on CT images as well as linking the Radiomics method with ML would categorize Lung Cancer commendably. 2023 IEEE. Creator An entity primarily responsible for making the resource Rajesh M.N.; Tanni N.; Baig Z.T. Source A related resource from which the described resource is derived Proceedings - International Conference on Technological Advancements in Computational Sciences, ICTACS 2023, pp. 1479-1485. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICTACS59847.2023.10389900" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICTACS59847.2023.10389900</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185375801&amp;doi=10.1109%2FICTACS59847.2023.10389900&amp;partnerID=40&amp;md5=9665b376df624cc13ae5ec4c50f819a0" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185375801&amp;doi=10.1109%2fICTACS59847.2023.10389900&amp;partnerID=40&amp;md5=9665b376df624cc13ae5ec4c50f819a0</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835034233-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rajesh M.N., Jain (Deemed-to Be-University), Electronics and Communication Engineering, Bengaluru, India; Tanni N., Christ (Deemed to Be University), B.Tech in Computer Science and Engineering (Data Science), Bengaluru, India; Baig Z.T., Amity University, Dept of It, Taskent, Uzbekistan