OBJECTIVE: To explore syndrome and treatment laws for treating diseases of the pulmonary system by establishing database based on clinical works by modern famous veteran doctors of Chinese medicine (CM). METHODS: Clinical experience and literature of medical records in clinical works by modern famous veteran doctors of CM were taken as data source. Database was established by fields and program design. On these bases, data mining methods such as frequency analysis, cluster analysis, factor analysis, and correlation laws were performed in syndrome and treatment laws for treating diseases of the pulmonary system. RESULTS: Established were database capable of literature searching, information statistics, data mining of modern famous veteran doctors of CM. A total of 34,414 data were input, including medical records and notes 28,045 items (81.49%) and clinical experience 6,369 items (18.51%). In medical records and notes, there were 14,048 items (50.09%) in male and 9,466 items (33.75%) in female, and the ratio of male to female was 1.48:1. There were 4,531 items (16.16%) with no marked gender in medical records or notes. Data mining such as correlation analysis, cluster analysis, factor analysis, correlation laws in more fields could be realized. CONCLUSIONS: Medical records and notes were dominated in data collected in this paper. The prevalence of pulmonary diseases was obviously higher in males than in females. The trend of concentrated manifestations in related fields for pulmonary diseases could be surfed by this database. Diagnosis and treatment laws for treating diseases of the pulmonary system could be found by various adaptive data mining targeting different fields. Multi-variables of symptoms, syndromes, prescriptions, and herbal drugs could be data mined in large samples of clinical literatures.
OBJECTIVE: To explore syndrome and treatment laws for treating diseases of the pulmonary system by establishing database based on clinical works by modern famous veteran doctors of Chinese medicine (CM). METHODS: Clinical experience and literature of medical records in clinical works by modern famous veteran doctors of CM were taken as data source. Database was established by fields and program design. On these bases, data mining methods such as frequency analysis, cluster analysis, factor analysis, and correlation laws were performed in syndrome and treatment laws for treating diseases of the pulmonary system. RESULTS: Established were database capable of literature searching, information statistics, data mining of modern famous veteran doctors of CM. A total of 34,414 data were input, including medical records and notes 28,045 items (81.49%) and clinical experience 6,369 items (18.51%). In medical records and notes, there were 14,048 items (50.09%) in male and 9,466 items (33.75%) in female, and the ratio of male to female was 1.48:1. There were 4,531 items (16.16%) with no marked gender in medical records or notes. Data mining such as correlation analysis, cluster analysis, factor analysis, correlation laws in more fields could be realized. CONCLUSIONS: Medical records and notes were dominated in data collected in this paper. The prevalence of pulmonary diseases was obviously higher in males than in females. The trend of concentrated manifestations in related fields for pulmonary diseases could be surfed by this database. Diagnosis and treatment laws for treating diseases of the pulmonary system could be found by various adaptive data mining targeting different fields. Multi-variables of symptoms, syndromes, prescriptions, and herbal drugs could be data mined in large samples of clinical literatures.