近年來人類疾病研究一直為全球生物醫學所關注的議題，許多研究聚焦在基因、蛋白質、藥物及代謝等不同維度建構基因網路、蛋白質與蛋白質間交互作用網路、藥物與蛋白質間交互作用網路、新陳代謝網路及疾病網絡來幫助我們瞭解疾病之間的關係。病歷是病患個人基本資料和就醫診療過程的記錄，利用醫院大量病人長時間就醫紀錄分析不同年齡層下疾病網路的差異性，藉由電子病歷及資料探勘技術所建立的醫院疾病表徵網路資料庫(Hospital Phenotypic Disease Network Database)。透過疾病表徵網路資料庫證明疾病表現與疾病盛行率會因為年齡及性別而有所不同。以建立的醫院疾病表徵網路資料庫據以建立臨床決策支援系統的知識庫，相信對於提高診斷之正確性及治療之最佳化有非常大的幫助，更可提昇醫療照護品質。;In recent years, using network theory to study human disease has been one of the major foci of the biomedical industry, including Gene Networks, Protein-Protein Interactions Network, Drug-Target Network and Metabolic Disease Network. These constructed Networks have helped us to understand the association between various cluster of diseases. The hospital electronic medical record, patient ICD9 codings, can be mined and analysis thus allowing us to constructed a Hospital Phenotypic Disease Network Database. Disease relationships can be queried in terms of gender and age. Disease comorbidities increases with age and also revealed a sexual dimorphic pattern in disease multi-morbidities. The Clinical Decision Support System can be build according by Hospital Phenotypic Disease Network Database can function as a clinical decision supporting system useful in enhancing the accuracy of diagnosis of comorbidities and thus providing timely appropriate treatment, and can improve the quality of healthcare.
