健康檢查為受檢者身體健康狀況最直接的依據，大部分醫院皆以該年度健檢結果進行分析解讀，卻忽略受檢者歷年累積之健檢報告的變化，為有效分析歷年健檢資訊，本研究將建置一健檢資料探勘系統，主要功能為：(1)個人歷年健檢資料查詢－提供醫師快速查詢受檢者歷年健檢報告；(2)各檢查項目趨勢圖－藉此發現各項目逐年遞增或遞減之數據，警示檢查項目屬於正常範圍但逐年趨於異常之情況；(3)健檢項目之關聯分析－藉此挖掘項目間潛在關聯性；(4)進階分析關聯法則－分析符合該關聯法則之受檢者是否存在某些特性。藉由本系統之分析結果顯示，確實發現某些項目間存有關聯性，且符合該關聯法則之受檢者皆具有某些特性，同時系統亦顯示出各檢查項目於各年度之變動情況。本系統提供之關聯分析結果及健檢變動趨勢確實可提供醫生做為輔助參考，並可藉由分析結果後提早告知受檢者潛在危險因子，以有效降低受檢者罹患疾病之可能性。

Regular health examination is the most direct way to realize the state of health. Unfortunately, most of the hospitals provide the medical explanation according to the single yearly examination result and ignore the overall analysis over past years. Hence, this investigation proposed a Health Mining System, whose main functions are: (1) Inquiry of personal history health information: provides doctors to quickly query the history health examination of patients, (2) Trend chart of examinations: makes the abnormal characteristics in personal health examination found and warned visually, (3) Association rule analysis of health examination: discovers the implied correlations in the mining and (4) Advanced association rule analysis: identifies the features of patients who correspond with specific association rule. The experimental results reveal that there exist correlations between some examinations certainly, and patients with the same correlations have the same medical characteristics indeed. The association rule analysis and health state trend of our system are able to assist the doctors in diagnosing and notify the patients about the potential risk factors in advance to reduce the possibility of having an illness.

摘要 I
Abstract II
誌謝 III
目錄 IV
圖表索引 VI
第1章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 5
1.3 研究流程 7
1.4 論文架構 8
1.5 研究範圍與限制 9
第2章 文獻探討 10
2.1 健康檢查概述 10
2.2 醫療資訊系統 23
2.3 資料探勘 28
2.4 關聯法則 35
第3章 研究方法 39
3.1 系統架構 39
3.2 資料預處理 41
3.3 關聯分析模組建立 48
3.4 FP-Growth演算法 51
3.5 個人健檢資料模組建立 56
第4章 系統實作 58
4.1 實作環境 58
4.2 資料來源 59
4.3 系統展示 61
4.4 結果分析 70
第5章 結論與未來研究方向 80
5.1 結論 80
5.2 未來研究方向 81
參考文獻 83
作者簡介 89

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