The outbreak of pneumonia caused by novel coronavirus (COVID-19) at the end of 2019 was a major public health emergency in human history. In a short period of time, Chinese medical workers have experienced the gradual understanding, evidence accumulation and clinical practice of the unknown virus. So far, National Health Commission of the People’s Republic of China has issued seven trial versions of the “Guidelines for the Diagnosis and Treatment of COVID-19”. However, it is difficult for clinicians and laymen to quickly and accurately distinguish the similarities and differences among the different versions and locate the key points of the new version. This paper reports a computer-aided intelligent analysis method based on machine learning, which can automatically analyze the similarities and differences of different treatment plans, present the focus of the new version to doctors, reduce the difficulty in interpreting the “diagnosis and treatment plan” for the professional, and help the general public better understand the professional knowledge of medicine. Experimental results show that this method can achieve the topic prediction and matching of the new version of the program text through unsupervised learning of the previous versions of the program topic with an accuracy of 100%. It enables the computer interpretation of “diagnosis and treatment plan” automatically and intelligently.
In order to understand the evolution of the diagnosis and treatment plans of corona virus disease 2019 (COVID-19), and provide convenience for medical staff in actual diagnosis and treatment, this paper uses the 9 diagnosis and treatment plans of COVID-19 issued by the National Health Commission during the period from January 26, 2020 to August 19, 2020 as research data to perform comparative analysis and visual analysis. Based on text mining, this paper obtained the text similarity and summarized its evolution law by expressing and measuring the similarity of the overall diagnosis and treatment plans of COVID-19 and the same modules, which provides reference for clinical diagnosis and treatment practice and other diagnosis and treatment plan formulation.