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Exploring syndrome differentiation using non-negative matrix factorization and cluster analysis in patients with atopic dermatitis
- Source :
- Computers in Biology and Medicine. 87:70-76
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- Syndrome differentiation (SD) results in a diagnostic conclusion based on a cluster of concurrent symptoms and signs, including pulse form and tongue color. In Korea, there is a strong interest in the standardization of Traditional Medicine (TM). In order to standardize TM treatment, standardization of SD should be given priority. The aim of this study was to explore the SD, or symptom clusters, of patients with atopic dermatitis (AD) using non-negative factorization methods and k-means clustering analysis. We screened 80 patients and enrolled 73 eligible patients. One TM dermatologist evaluated the symptoms/signs using an existing clinical dataset from patients with AD. This dataset was designed to collect 15 dermatologic and 18 systemic symptoms/signs associated with AD. Non-negative matrix factorization was used to decompose the original data into a matrix with three features and a weight matrix. The point of intersection of the three coordinates from each patient was placed in three-dimensional space. With five clusters, the silhouette score reached 0.484, and this was the best silhouette score obtained from two to nine clusters. Patients were clustered according to the varying severity of concurrent symptoms/signs. Through the distribution of the null hypothesis generated by 10,000 permutation tests, we found significant cluster-specific symptoms/signs from the confidence intervals in the upper and lower 2.5% of the distribution. Patients in each cluster showed differences in symptoms/signs and severity. In a clinical situation, SD and treatment are based on the practitioners' observations and clinical experience. SD, identified through informatics, can contribute to development of standardized, objective, and consistent SD for each disease.
- Subjects :
- Adult
Male
Pediatrics
medicine.medical_specialty
Adolescent
Health Informatics
Disease
Dermatitis, Atopic
Non-negative matrix factorization
Young Adult
03 medical and health sciences
0302 clinical medicine
Republic of Korea
medicine
Cluster Analysis
Humans
In patient
Young adult
Child
Syndrome differentiation
business.industry
Atopic dermatitis
medicine.disease
Confidence interval
030205 complementary & alternative medicine
Computer Science Applications
Child, Preschool
030220 oncology & carcinogenesis
Informatics
Female
business
Algorithms
Subjects
Details
- ISSN :
- 00104825
- Volume :
- 87
- Database :
- OpenAIRE
- Journal :
- Computers in Biology and Medicine
- Accession number :
- edsair.doi.dedup.....f8d5a1f86b00c35dfeccb2df183a03ca