Methods and systems for using artificial intelligence to select a compatible element

A method for using artificial intelligence to select a compatible element, the method comprising:

• receiving, by at least a server, training data, wherein receiving the training data further comprises receiving a first training set including a plurality of first data entries, each first data entry of the plurality of first data entries comprising at least an element of physiological state data and at least a correlated compatible label;
• receiving, by the at least a server, a biological extraction from a user, wherein the biological extraction relates to a medical condition of the user;
• filtering, by the at least a server, elements of the training data using a natural language processing algorithm to generate a plurality of filtered training data sets each containing a plurality of data entries categorizing training data elements to categories of biological extractions;
• selecting, by the at least a server, at least one filtered training data set of the plurality of filtered training data sets as a function of the medical condition of the user using the natural language processing algorithm;
• receiving, by the at least a server, a datum of user activity data, wherein the datum of user activity comprises a list of activities and compatible elements associated with the user;
• updating, by the at least a server, the selected and filtered at least one training data set with previous user interactions, wherein the previous user interactions comprise a past purchase history of the user;
• training, by the at least a server, a machine-learning model iteratively using the updated, selected and filtered at least one training data set, wherein the machine-learning model is a neural network, wherein training the machine-learning model further comprises:
• selecting a portion of the updated, selected and filtered at least one training data set as a function of a user cohort;
• adjusting weights of relationships between the at least an element of physiological state data and the at least a correlated compatible label using the selected portion of the updated, selected and filtered at least one training data set;
• and
• generating a multidimensional feature vector representation of the physiological state data and propagating the multidimensional feature vector representation through at least one hidden layer of the neural network to compute an output activation corresponding to the correlated compatible label;
• generating, using the trained machine-learning model, a compatible element index,
• wherein the compatible element index is a value assigned to a compatible element based on previous user interactions;
• selecting, by the at least a server using the trained machine-learning model, at least a compatible element as a function of the compatible element index generated using the neural network, the biological extraction, and the selected portion of the updated, selected and filtered at least one training data set;
• and
• transmit the at least a compatible element to a user client device wherein the user client device comprises a display in communication with the at least a server.