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  • 學位論文

應用案例式推理於血液透析品質評估之輔助系統研究

Using Case Based Reasoning for Assistance in Hemodialysis Quality Support System

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摘要


根據民國94年中華民國腎臟基金會統計全台資料顯示得知,目前需藉由長期透析方式維持健康之末期腎臟病患(End Stage Renal Disease,ESRD)已高達45,718人,其中接受血液透析病患有41,905人,可見血液透析仍是目前末期腎臟病患主要之選擇。台灣透析病患有95.8%需要每週進行三次血液透析,每次透析約需四至五小時,故大部分透析病患之生活品質會受到很大的影響。 尿毒症是腎臟功能極度衰竭引起的症候群,病患必須依靠長期透析治療維持生命。然而,透析治療期間時常發生電解質不平衡及體液的累積,導致病患不適而產生長期透析症候群,甚至引發急性併發症導致死亡。如何讓透析治療除了延續生命以外,提昇到生活品質的訴求,血液透析品質對病患而言不容忽視。 本研究開發「血液透析品質評估輔助系統」,對於血液透析品質有分辨(差、普通、好、很好)的能力。利用長期血液透析累積大量檢驗數據,及相關醫學文獻找出血液透析品質指標:Kt/V、URR、Albumin、Hct,建立血液透析品質因子。藉由案例式推理之運用,建立系統,以及運用粒子搜尋法(Particle Swarm Optimization,PSO)決定案例式推理裡各因子最佳的權重,結果顯示準確度為81.1321%,此系統可提供醫護人員臨床照護參考,對病患狀況作預先處置,使達到適化透析的境界,對透析病患將是一大助益。

關鍵字

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並列摘要


Uremia is a symptom occurred by kidneys’ exhaustion. The patient needs long-term dialysis to prolong his life. However, the electrolyte’s disequilibria and the body fluid’s accumulation arisen in the long-term dialysis lead the patient to discomfort, and even to dead. It’s not disregarding for the patient that take which way to prolong his life and improve his life quality further. In this paper, we develop fuzzy Dialysis Quality Evaluation Support System, which has the capability to distinct the dialysis quality(bad, normal, good, excellent). Use the large amount of experiment values, which come from the long-term accumulated dialysis, we studying the medical research and interviewing to the related experts, and find out the dialysis-quality indexes: Kt/V, URR, Albumin, Hct. Further, we use Case Based Reasoning to set up the system and use Particle Swarm Optimization to search the optimal weighting of index to provide the useful information for the medical workers serving in clinical care. The result shows that the accuracy of Case Based Reasoning system reached 81.1321%. It will be helpful for the patient if we can predict the patient’s condition and take the proper treatment, we may prevent his illness getting worse and reach the state of the appropriate dialysis treatment.

並列關鍵字

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參考文獻


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