Misdiagnosis features of ancient clinical records based on apriori algorithm

• Main Author: Ling Yu
• Format: Article
• Language: English
• Published: Wolters Kluwer Medknow Publications 2020-01-01
• Series: Chinese Medicine and Culture
• Subjects: ancient clinical cases; apriori algorithm; classified medical cases of famous physicians; data mining; misdiagnosis features; supplement to classified case records of celebrated physicians
• Online Access: http://www.cmaconweb.org/article.asp?issn=2589-9627;year=2020;volume=3;issue=1;spage=50;epage=53;aulast=Yu

Objective: To analyze misdiagnosis features in clinical cases of “Classified Medical Cases of Famous Physicians” and “Supplement to Classified Case Records of Celebrated Physicians.” Materials and Methods: Two hundred and five ancient misdiagnosed cases were analyzed in aspects of locations (exterior-interior type, qi-blood type and Zang-Fu organs type) and patterns (heat-cold type and deficiency-excess type) by Apriori Algorithm Method. Results: The main types of misdiagnosis in those medical casesare as follows:: Zang-Fu location misjudgment, misjudging the interior as the exterior, misjudging deficiency pattern as excess pattern, and misjudging cold pattern as heat pattern. Among them, the most outstanding type is the misjudgment of deficiency–cold pattern as excess–heat pattern. Conclusions: (1) Accurate judgment of location and differentiation of deficiency and excess patterns are the key points in diagnosing the diseases correctly. The confusion of true deficiency–cold and pseudo-excess–heat pattern should be taken seriously. (2) Data mining on ancient clinical cases offers a new methodology for assisting clinical diagnosis of traditional Chinese medicine.