Abstract
Tongue analysis is an efficient indicative strategy for assessing the state of the internal organs and to detect associated diseases. In this study, the tongue diagnosis is carried out by evaluating photographs of the tongue. Feature extraction from tongue captured images, obtaining features such as texture, color and geometry which is then used to train classification models that detect associated diseases. Essentially, this paper aims to understand the patients which are healthy or are diagnosed with several diseases using the image of tongue.
The secondary objective is to perform comparative analysis of machine learning algorithms to seek out the efficient performing models and their differences in hope to achieve better performance than those which have been achieved till date.
This automated tongue analysis is not meant to replace every day diagnostic practices. It is meant to help the doctor in making their decisions by providing a prior warning signal that will aid in an X-ray or CT scan conclusion if further diagnosis is needed through other methods.
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Wankhede, D.S., Pandit, S., Metangale, N., Patre, R., Kulkarni, S., Minaj, K.A. (2022). Survey on Analyzing Tongue Images to Predict the Organ Affected. In: Abraham, A., et al. Hybrid Intelligent Systems. HIS 2021. Lecture Notes in Networks and Systems, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-030-96305-7_56
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DOI: https://doi.org/10.1007/978-3-030-96305-7_56
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