A method for generating a software-implemented module configured to determine concentration of an analyte in a sample of a bodily fluid, the method comprising, in one or more data processing devices, - providing a first set of measurement data, the first set of measurement data representing first color information derived by image data processing from images for a region of interest of one or more test strips, the images - being indicative of a color transformation of the region of interest in response to applying one or more first samples of a bodily fluid containing an analyte to the region of interest; and - recorded by a plurality of devices each configured for image recording and image data processing for generating the first color information, the plurality of devices provided with different software and / or hardware device configuration applied for image recording and image data processing in the device; - generating a neural network model in a machine learning process applying an artificial neural network, comprising - providing the neural network model; - creating training data, validation data and test data from the first set of measurement data; and - training the neural network model by the training data, wherein the training data represent a full population of the plurality of devices and experiment types; and - generating a software-implemented module comprising a first analyzing algorithm representing the neural network model; wherein the software-implemented module is configured to, when loaded into a data processing device having one or more processors, determine concentration of an analyte in a second sample of a bodily fluid from analyzing a second set of measurement data indicative of second color information derived by image processing from images for a region of interest of one or more test strips, the images being indicative of a color transformation of the region of interest in response to applying the second sample of the bodily fluid containing the analyte to the region of interest. - providing a first set of measurement data, the first set of measurement data representing first color information derived by image data processing from images for a region of interest of one or more test strips, the images - being indicative of a color transformation of the region of interest in response to applying one or more first samples of a bodily fluid containing an analyte to the region of interest; and - recorded by a plurality of devices each configured for image recording and image data processing for generating the first color information, the plurality of devices provided with different software and / or hardware device configuration applied for image recording and image data processing in the device; - being indicative of a color transformation of the region of interest in response to applying one or more first samples of a bodily fluid containing an analyte to the region of interest; and - recorded by a plurality of devices each configured for image recording and image data processing for generating the first color information, the plurality of devices provided with different software and / or hardware device configuration applied for image recording and image data processing in the device; - generating a neural network model in a machine learning process applying an artificial neural network, comprising - providing the neural network model; - creating training data, validation data and test data from the first set of measurement data; and - training the neural network model by the training data, wherein the training data represent a full population of the plurality of devices and experiment types; and - providing the neural network model; - creating training data, validation data and test data from the first set of measurement data; and - training the neural network model by the training data, wherein the training data represent a full population of the plurality of devices and experiment types; and - generating a software-implemented module comprising a first analyzing algorithm representing the neural network model;