A testing method for determining metabolite quantities of a test strip using a testing system comprising: a smart device having a camera, a wireless communication module, a screen, a processor and a memory storing the parameters and structure of a learning model determined in the training method comprising the steps of: - exposing a test strip to a biological sample, - measuring metabolite quantities of the test strip using the biochemistry analyzer, - acquiring a set of images containing same test strip by the data augmentation device simulating ambient lighting conditions using light sources, - extracting the images of the test strip from the set of the images by the computer system, - saving the extracted images of the test strip with the corresponding metabolite quantity information measured by the analyzer to a storage media as training samples, - training a learning model to determine parameters of the learning model using the training samples stored in the storage media by the computer system, - transferring the parameters and the learning model to a remote server via the wireless communication unit to store them, the testing method comprising the steps of: - capturing and storing a plurality of images containing a test strip using the smart device, - pre-processing the images by extracting the images of the test strip from the captured images, - classifying the standardized images of the test strip using the learning model structure and parameters to assign metabolite values, - combining the values of the test strips and determining the final metabolite quantities, - displaying the final metabolite quantities on the screen of the smart device and characterized by standardizing the pre-processed images in the step of "pre-processing the images by extracting the images of the test strip from the captured images " in terms of the size and the aspect ratio. - exposing a test strip to a biological sample, - measuring metabolite quantities of the test strip using the biochemistry analyzer, - acquiring a set of images containing same test strip by the data augmentation device simulating ambient lighting conditions using light sources, - extracting the images of the test strip from the set of the images by the computer system, - saving the extracted images of the test strip with the corresponding metabolite quantity information measured by the analyzer to a storage media as training samples, - training a learning model to determine parameters of the learning model using the training samples stored in the storage media by the computer system, - transferring the parameters and the learning model to a remote server via the wireless communication unit to store them, the testing method comprising the steps of: - capturing and storing a plurality of images containing a test strip using the smart device, - pre-processing the images by extracting the images of the test strip from the captured images, - classifying the standardized images of the test strip using the learning model structure and parameters to assign metabolite values, - combining the values of the test strips and determining the final metabolite quantities, - displaying the final metabolite quantities on the screen of the smart device and characterized by standardizing the pre-processed images in the step of "pre-processing the images by extracting the images of the test strip from the captured images " in terms of the size and the aspect ratio. - capturing and storing a plurality of images containing a test strip using the smart device, - pre-processing the images by extracting the images of the test strip from the captured images, - classifying the standardized images of the test strip using the learning model structure and parameters to assign metabolite values, - combining the values of the test strips and determining the final metabolite quantities, - displaying the final metabolite quantities on the screen of the smart device and characterized by standardizing the pre-processed images in the step of "pre-processing the images by extracting the images of the test strip from the captured images " in terms of the size and the aspect ratio.