在雲端醫療知識平台運用關聯規則與語意網技術

近年來巨量資料(Big Data)使得雲端運算(Cloud Computing)備受重視，透過人工智慧(Artificial Intelligence)提供更有價值的資訊。健康是人生重要的財富，醫院業者透過衛教單提供醫療知識給需要的人，但是目前衛教單都是以紙張的方式呈現，不僅浪費資源也只能被動地等待需要的人來拿取，無法達到主動推薦以及延伸推薦衛教單給需要的人，論文提出一個整合語意網(Semantic Web)與關聯規則(Association Rule)技術基於雲端運算架構(Integrating Semantic Web and Association Rule base on Cloud Computing Framework, ISWARCCF)來解決上述之問題。在此建構一個雲端醫療知識平台(Cloud Medical Knowledge Platform, CMKP)，開發一個手機App與網頁平台來呈現資料，並將健康存摺、衛教單、開放資料(Open Data)做為資料來源，在雲端運算Spark上進行語意網與關聯規則技術智能化的推論。將衛教單結合電子圖書標準的EPUB格式，再以健康存摺系統裡的就診紀錄當作推薦的依據，透過語意網能夠主動推薦適合使用者的EPUB衛教單以及推論出敏感性患者額外的個人外出建議，此外使用100份的常見疾病與癌症閱讀關聯之問卷調查當作資料來源，透過關聯規則找出疾病與疾病之間的關聯性，產生出新的規則並結合語意網推論出新的事實，達到推薦其他延伸的EPUB衛教單給使用者，而在巨量資料的時代裡透過Spark加速資料的運算，本論文以CMKP來驗證ISWARCCF的可行性以及解決上述所說衛教單之問題。

關鍵字

巨量資料；雲端運算；人工智慧；語意網；關聯規則；開放資料； EPUB

並列摘要

The big data brings public attention to cloud computing in recent years, which provides more valuable information through artificial intelligence. Health is critical wealth for one’s life. The hospitals use the Patient Education to provide the medical care knowledge for those in need. However, the paper Patient Education causes resource waste and can be only taken by others passively. It can’t achieve the purpose of proactive promotion and extend it to those in need. This paper proposes Integrating Semantic Web and Association Rule based on Cloud Computing Framework (ISWARCCF) to resolve the above issue. It builds a Cloud Medical Knowledge Platform (CMKP) and develops a mobile App and webpage platform for data display. Moreover, it takes the health bank, Patient Education, and open data as CMKP data source. The data inference is performed through semantic web and association rule, and the computing is performed on Spark. With the above technologies, it sets up the CMKP architecture. After electronic data and integration with e-book EPUB technology, the Patient Education becomes an e-book in the format of EPUB. Then it takes the medical record in the health bank system as the recommendation foundation. Through semantic web, it proactively recommends the EPUB Patient Education suitable for the user and infers the additional personal advice for certain patients. Besides, it takes 100 questionnaires of common disease and cancer reading association as the data source to find out the correlation among the diseases through association rule. In this way, it generates new rules and combines with semantic web to infer new facts, so as to achieve the purpose of recommending other extended EPUB Patient Education to users. In the era of big data, the data computing can be faster through Hadoop HDFS storage file system and Spark RDD parallel computing. This paper applies CMKP to verify the feasibility of ISWARCCF and resolve the problem of Patient Education as stated above.

並列關鍵字

Big Data ； Cloud Computing ； Artificial Intelligence ； Semantic Web ； Association Rule ； Open Data ； EPUB

參考文獻

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在雲端醫療知識平台運用關聯規則與語意網技術

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