DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-12,Issue-5 ( May, 2024 ) | |||||||||
Paper Title |
Thyroid Cancer Detection Using Deep Learning Techniques | |||||||||
Author Name |
T. Anjibabu, Leelavathi Arepalli, N. S S D Pavan, M. P S Kishore, Ch. Gowtham Kumar, M. Nitish | |||||||||
Affilition |
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Pages |
12-16 | |||||||||
Abstract |
This paper introduces an effective diagnostic strategy for thyroid cancer using a CNN based deep learning model. A user-friendly Flask web application facilitates secure transmission of medical reports, including thyroid images, for precise analysis. The CNN demonstrates high accuracy in predicting thyroid cancer severity levels, offering healthcare professionals clear and timely insights for informed decision-making in intervention and treatment planning. This approach signifies a significant step forward in leveraging CNN technology for enhanced thyroid cancer detection. Keywords - Thyroid Cancer, Convolution Neural Network, Deep Learning Model, Decision Making, Severity Level | |||||||||
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