人工智慧機器學習在重症照護單位的應用

10.6666/ClinMed.202102_87(2).0015

盧紀婷；周睿信；林祐霆；黃柏勳

人工智慧（artificial intelligence） ； 機器學習（machine learning） ； 波型分析（waveform analysis） ； 重症照護單位（intensive care unit）

臨床醫學月刊

87卷2期（2021 / 02 / 26）

97 - 106

繁體中文

人工智慧此一概念提出後已經歷半個世紀，近年來人工智慧更乘著機器學習及深度學習的名目蓬勃發展。人工智慧應用於心血管疾病和重症病人的數據資料分析是一個持續進展的領域，隨著生物資訊學的進展，有越來越多利用人工智慧和機器學習建置的模型，用來預測重症病患心律不整、急性腎損傷、敗血症、休克等不良事件的發生率。在加護病房，我們會常規使用生理監測儀器監測重症病人的心電圖、血壓、血氧濃度等波型訊號。傳統上我們會將連續性的波型訊號轉換或截取為數值資料加以紀錄，用來判斷病人的病情變化。目前已知的人工智慧的預測模型，大多是輸入數值型資料或是圖形，以監督式機器學習的方式來建構預測模型。這會忽略部分細微和早期的波型變化，殊為可惜。在重症醫學領域，輸入和分析波型數據資料的人工智慧模型仍非常稀少。本文將概述人工智慧應用於重症病人的現況，並簡介非監督式流型波型數據分析此一最新的生理訊號波型分析方法。

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