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 Book Chapter Book Chapter Faculty Publications- Book Chapter 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 Insights into thyroid disease: Harnessing machine learning for analysis and classification of multi-label medical data Description An account of the resource Thyroid disease refers to a wide range of disorders that occur due to dysfunction of the thyroid gland, a small gland located at the base of the neck that produces thyroid hormones. Through the analysis of this comprehensive dataset, we aim to utilize machine learning (ML) techniques for the analysis and classification of thyroid data. Employing ML techniques for thyroid classification has the potential to improve diagnostic accuracy, facilitate timelier interventions, lower expenses, optimize doctor time, and foster a more personalized approach to thyroid care. The objective of this research was to conduct multiclassification, encompassing the broadest array of classes for the target variable. To address the imbalances within the dataset, we employed the Synthetic Oversampling Technique (SMOTE) as a resampling method. Specifically, classes with a minimum of 10 samples were retained, resulting in the inclusion of 19 out of the total 34 classes in the dataset. The importance of SMOTE in addressing class imbalance is examined in this chapter, with an emphasis on how it may be used to enhance classifier model performance. Moreover, we conducted a comparative analysis of Classification Models, including Random Forest, K-Nearest Neighbor, Decision Tree, SVM, Gradient Boosting, Multinomial Naive Bayes, and Logistic Regression, to assess their accuracies. Following the resampling of the dataset, the highest accuracy of 99.99% was achieved with the gradient booster. Additionally, this research incorporated the association rule technique to uncover meaningful relationships within the dataset. 2025 selection and editorial matter, Arun Kumar Rana, Vishnu Sharma, Sanjeev Kumar Rana, and Vijay Shanker Chaudhary; individual chapters, the contributors. All rights reserved. Creator An entity primarily responsible for making the resource Surendran S.; Salma M.U. Source A related resource from which the described resource is derived Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering, pp. 54-69. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003476207-4" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003476207-4</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206540661&amp;doi=10.1201%2F9781003476207-4&amp;partnerID=40&amp;md5=28af2a28463535e41215db79d03cfc79" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206540661&amp;doi=10.1201%2f9781003476207-4&amp;partnerID=40&amp;md5=28af2a28463535e41215db79d03cfc79</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-104014934-8; 978-103275923-4 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 Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Surendran S., Christ(Deemed to Be University), Bengaluru, India; Salma M.U., Department of Statistics and Data Science, Christ(Deemed to Be University), Bengaluru, India