Automated Diagnosis to Predict the Thyroid Using Machine Learning Algorithms

International Journal of Electrical and Electronics Engineering

© 2024 by SSRG - IJEEE Journal

Volume 11 Issue 12

Year of Publication : 2024

Authors : Meenakshi Thalor, Mrunal Pathak, Vandana Kale, Veena Bhende

10.14445/23488379/IJEEE-V11I12P129

How to Cite?

Meenakshi Thalor, Mrunal Pathak, Vandana Kale, Veena Bhende, "Automated Diagnosis to Predict the Thyroid Using Machine Learning Algorithms," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 12, pp. 308-313, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I12P129

Abstract:

Thyroid disorders affect millions worldwide, necessitating early and accurate diagnosis to ensure effective management and treatment. In this context, the Thyroid Stage Prediction App represents a groundbreaking healthcare innovation. This mobile application leverages cutting-edge machine learning technologies to accurately predict thyroid stage progression, offering a proactive approach to thyroid disease management. The Thyroid Stage Estimator app features an intuitive interface that lets users access their medical history, test results, and related symptoms easily. The app then processes this information using algorithms to measure current thyroid levels and predict future growth. This predictive model is based on a large database of non-patient information and is continually updated to ensure reliability and accuracy. Key features of the app include stage estimation, personalized recommendations, reminders to consult with doctors, and encouragement of early intervention and treatment plans. The app also provides important information about thyroid health and wellness, allowing users to make informed decisions about their health.

Keywords:

Logistic regression, Machine Learning, Random forest, Support Vector Machine, Thyroid.

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