Studying Artificial Intelligence Neural Network Based TCM Diagnosis and Treatment Information Management System

Traditional Chinese medicine is a priceless legacy of Chinese medicine that has developed over thousands of generations of practical accumulation into a whole medical system with a distinctive theoretical foundation and extensive clinical experience. However, because of its heavy reliance on diagnostic experience, it is unsuitable for management and advancement. The idea of digital medicine is therefore progressively becoming more broadly recognised, particularly in the area of medical diagnostics. The effectiveness and precision of medical diagnosis directly affect people’s lives and health, making it a critical problem that cannot be disregarded. In order to accomplish the goal of Traditional Chinese medicine (TCM) diagnosis, an expert system is constructed using the continuously expanding case base as the knowledge basis for reasoning. The purpose of this study is to use artificial neural networks (ANNs), which have great learning, adaptability, and massively parallel processing capabilities, to deal with tough, unstructured, nonlinear problems in management information systems. Following an experimental investigation, the total error of the modified system is decreased by around 75.3%, and the average forecast precision near 75%. The back propagation (BP) algorithm is upgraded to optimise the inaccuracy of the weight, repair, or energy parameters in order to achieve this.