IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

A Literature Review on Thyroid Hormonal Problems in Women Using Data Science and Analytics: Healthcare Applications

A Literature Review on Thyroid Hormonal Problems in Women Using Data Science and Analytics: Healthcare Applications
View Sample PDF
Author(s): R. Suganya (Thiagarajar College of Engineering, India), Rajaram S. (Thiagarajar College of Engineering, India)and Kameswari M. (Thiagarajar College of Engineering, India)
Copyright: 2021
Pages: 13
Source title: Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics
Source Author(s)/Editor(s): Bhushan Patil (Independent Researcher, India)and Manisha Vohra (Independent Researcher, India)
DOI: 10.4018/978-1-7998-3053-5.ch021

Purchase


Abstract

Currently, thyroid disorders are more common and widespread among women worldwide. In India, seven out of ten women are suffering from thyroid problems. Various research literature studies predict that about 35% of Indian women are examined with prevalent goiter. It is very necessary to take preventive measures at its early stages, otherwise it causes infertility problem among women. The recent review discusses various analytics models that are used to handle different types of thyroid problems in women. This chapter is planned to analyze and compare different classification models, both machine learning algorithms and deep leaning algorithms, to classify different thyroid problems. Literature from both machine learning and deep learning algorithms is considered. This literature review on thyroid problems will help to analyze the reason and characteristics of thyroid disorder. The dataset used to build and to validate the algorithms was provided by UCI machine learning repository.

Related Content

N. Geethanjali, K. M. Ashifa, Avantika Raina, Jayashree Patil, Rameshwaran Byloppilly, S. Suman Rajest. © 2024. 19 pages.
Praveen Kakada, Muhammed Shafi M. K.. © 2024. 14 pages.
P. S. Venkateswaran, Divya Marupaka, Sachin Parate, Amit Bhanushali, Latha Thammareddi, P. Paramasivan. © 2024. 15 pages.
M. Lishmah Dominic, P. S. Venkateswaran, Latha Thamma Reddi, Sandeep Rangineni, R. Regin, S. Suman Rajest. © 2024. 15 pages.
S. Sivabala, P. Vidyasri. © 2024. 23 pages.
H. Hajra, G. Jayalakshmi. © 2024. 22 pages.
Anusha Thakur. © 2024. 15 pages.
Body Bottom