In Deep Learning Classifier.
it is best to use images and let the algorithm quantify its own tabular data. the more images you train the more precise results you get
The below articles may help you
https://towardsdatascience.com/integrating-image-and-tabular-data-for-deep-learning-9281397c7318
Article Machine-Learning-Based Disease Diagnosis: A Comprehensive Review
Article Visual Tea Leaf Disease Recognition Using a Convolutional Ne...
I think it depends upon the type of disease. Some are value-centric and some are visual centric.
Booth are commenly used, however., for the case of data mining people use tabular data, whilst for computer vision applications, images data is efficient and usual.
Is it possible to find in fluent? Any other method is there?
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