Research of insomnia on traditional Chinese medicine diagnosis and treatment based on machine learning

Abstract

Background Insomnia as one of the dominant diseases of traditional Chinese medicine (TCM) has been extensively studied in recent years. To explore the novel approaches of research on TCM diagnosis and treatment, this paper presents a strategy for the research of insomnia based on machine learning. Methods First of all, 654 insomnia cases have been collected from an experienced doctor of TCM as sample data. Secondly, in the light of the characteristics of TCM diagnosis and treatment, the contents of research samples have been divided into four parts: the basic information, the four diagnostic methods, the treatment based on syndrome differentiation and the main prescription. And then, these four parts have been analyzed by three analysis methods, including frequency analysis, association rules and hierarchical cluster analysis. Finally, a comprehensive study of the whole four parts has been conducted by random forest. Results Researches of the above four parts revealed some essential connections. Simultaneously, based on the algorithm model established by the random forest, the accuracy of predicting the main prescription by the combinations of the four diagnostic methods and the treatment based on syndrome differentiation was 0.85. Furthermore, having been extracted features through applying the random forest, the syndrome differentiation of five zang-organs was proven to be the most significant parameter of the TCM diagnosis and treatment. Conclusions The results indicate that the machine learning methods are worthy of being adopted to study the dominant diseases of TCM for exploring the crucial rules of the diagnosis and treatment.

Medication rule of Professor Li Jun in the Treatment of Insomnia Based on Traditional Chinese Medicine Inheritance Auxiliary Platform System

“…Western medicine diagnosis was based on the diagnostic criteria of the Chinese Guidelines for the Diagnosis and Treatment of Insomnia (2017). Insomnia is a sleep disorder characterized by frequent and persistent difficulty in falling asleep and/or difficulty in maintaining sleep and causing an unsatisfactory sleep sensation [6].…”

Design of TCM detection information platform based on Artificial Intelligence

“…The literature uses hierarchical clustering, factor analysis and other methods in machine learning to quantitatively analyze the information and syndromes of the four diagnoses of traditional Chinese medicine, and uses explicit and latent variable factor models to test the information of the four diagnoses of hypertension, and analyzes the relationship between the syndromes [8]. By analyzing the collected 1501 typical cases of hypertension, a model of TCM assisted diagnosis and treatment was established [9]. By applying machine learning methods to the quanti cation process of traditional Chinese medicine, the diagnostic criteria of traditional Chinese medicine syndromes will no longer be based on the judgment of doctors, but have a more scienti c and standardized quantitative description and a more reasonable explanation of the laws of traditional Chinese medicine [10].…”

“…Write the generated m n-dimensional feature vectors as n × m-dimensional data array. Matrix E is normalized according to formula (9), and matrix 𝑬 * = (𝐸 ij *) n × m is the normalization matrix to eliminate the interference of data volume. 9…”

Perceptions of traditional Chinese medicine doctors about using wearable devices and traditional Chinese medicine diagnostic instruments: A mixed-methodology study

“… 15 – 16 In recent years, several studies have summarized the characteristics of symptoms in TCM and found that diagnosis in TCM can be achieved by bionics instruments. 17 – 19 The application of ICT in the field of medicine and health has become normal, and several TCM doctors have begun using devices as diagnostic tools.…”