Methods and systems for identifying a causal link

A system for identifying a causal link including a computing device wherein the computing device further comprises one or more network interfaces and one or more processors, the system comprising:

• a diagnostic generator module operating on the computing device, the diagnostic generator module designed and configured to:
• receive a first user symptom datum from a user client device associated with a user wherein the first user symptom datum includes a current medical indicator;
• receive diagnostic training data from a machine-learning database correlating symptom data to prognostic data;
• and
• generate, using a supervised machine-learning process, a diagnostic model that receives the first user symptom datum as an input and produces an output containing a first prognosis;
• a prognostic chaining module operating on the computing device, the prognostic chaining module designed and configured to:
• receive an expert input dataset from an expert knowledge database wherein the expert input dataset comprises an expert journal article identifying prognostic data correlated to causal link data;
• receive the first user symptom datum and the first prognosis from the diagnostic generator module;
• generate a gaussian mixture clustering model utilizing the expert input dataset and the first prognosis and outputting a defined number of clusters;
• and
• identify a first causal link associated with the user chained to the first prognosis as a function of generating the gaussian mixture clustering model;
• and
• a causal link module operating on the computing device, the causal link module designed and configured to:
• receive from the prognostic chaining module the first prognosis chained to the first causal link associated with the user, wherein the first causal link identifies a root cause of the first prognosis;
• receive from the prognostic chaining module a second prognosis chained to a second causal link associated with the user, wherein the second causal link identifies a root cause of the second prognosis;
• and
• evaluate the first causal link and the second causal link to calculate a degree of similarity between the first causal link and the second causal link, wherein evaluating the first causal link and the second causal link comprises generating a recommendation for further testing as a function of the degree of similarity and displaying the recommendation for further testing at an advisor client device.