Deep Learning Techniques for Oral Diagnosis and Cavity Recognition : A systematic Approach

  • Shashikant Patil, Smita Nirkhi

Abstract

This is an attempt to review and address the various issues in the diagnostic test accuracy of caries detection using image processing techniques. This study is carried out with a sole objective to o undertake a comprehensive assessment to establish the diagnostic accuracy in the detection and diagnosis of dental caries using image processing techniques along with expert systems and knowledge based systems. We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for image processing techniques for dental caries detection. While carrying the content review, we understood that deep learning performs better for big and varied datasets than classic analysis and machine classification methods. Deep learning algorithms try to develop the model by using all the available input. This paper provides the comparative analysis of different machine learning algorithms for diagnosis of different diseases such in dental imaging and image processing. It brings thoughtfulness concerning the collection of machine learning procedures and tools that are used for the investigation of ailments and decision-making process consequently.

Published
2020-05-01
How to Cite
Shashikant Patil, Smita Nirkhi. (2020). Deep Learning Techniques for Oral Diagnosis and Cavity Recognition : A systematic Approach. International Journal of Advanced Science and Technology, 29(9s), 192 - 199. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/13024