An Automatic Disease Diagnosis Method Based on Big Medical Data

Medical diagnoses automation based on huge data is of great significance to doctor-patient contradiction regulation and the optimizing allocation of health resources. This paper presents an intelligent automatic disease diagnosis system. Based on a large number of confirmed disease cases, the method of probability and statistics is used to find the relations between the symptoms and different diseases, the confirmed symptom sets of different diseases are obtained first, and then the diagnoses are given by examining that how many symptoms are both in the symptoms provided by patients and the confirmed symptom sets of different diseases. The automatic disease diagnoses system has been implemented preliminarily and the system is proved having some value in clinical application.