Abstract: A simple urine flow test result learning method and a lower urinary tract symptom diagnosis method is provided, and more particularly, a simple urine flow test result learning method and a lower urinary tract symptom diagnosis method of training a neural network using simple urine flow test results, which are non-invasive data, and diagnosing lower urinary tract symptoms using the trained neural network, wherein the lower urinary tract symptom diagnosis method prevents pain and shame from occurring in a patient during a diagnosis process of lower urinary tract symptoms and reduces the risk of secondary infection occurring through an invasive diagnosis method, by generating a trained model using results of a simple urine flow test, which is a non-invasive test method, based on deep learning, and diagnosing lower urinary tract symptoms using the trained model.

Abstract: A method for supporting diagnosis of LUTS may include: receiving urinary system data of an examinee; deriving prediction result data for the examinee by using an LUTS prediction model for the received urination system data; and providing the derived prediction result data to a user terminal.