Authors : Amith B; Harshitha KN; Vijay R; Meghana B R; Dr. Shivandappa; Dr. Narendra Kumar S

Volume/Issue : Volume 9 - 2024, Issue 9 - September

Google Scholar : https://tinyurl.com/8sbnf6jx

Scribd : https://tinyurl.com/w8ysy4x6

DOI : https://doi.org/10.38124/ijisrt/IJISRT24SEP0229

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This research paper is a novel fever detection methodology using the image classification technique with Python-based convolutional neural networks. We have developed a non-invasive and efficient method to identify fever by analysing images of the tongue, based on traditional Chinese medicine. Later on, we built a model which gave 92.2% on the test set with labelled data of images of the tongues. This model obtains better performance from more advanced pre-processing techniques, such as normalization and data augmentation. This study indicates that an integration between ancient diagnostic methods and the latest machine learning algorithms may open new horizons in fever diagnosis during medical practices. Finally, the use of this technology in mobile health applications will promote early treatment, reduce complications, and avoid the need for more complicated interventions.

Keywords : Fever Detection, Image Classification, Convolutional Neural Networks (CNN), Non-Invasive Diagnosis, Traditional Chinese Medicine, Tongue Analysis, Machine Learning, Data Pre-Processing, Normalization, Data Augmentation, Mobile Health Applications, Early Treatment, Medical Diagnostics, Advanced Algorithms, Health Technology Integration.

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