研究目的
隨著醫療科技的進步，造就並融入了人工智慧。根據台灣衛生福利部統計，腦血管相關疾病在2019年台灣十大死因佔居第四名，排名順位近5年來相同，由此可知腦血管疾病一直影響國人健康。故本研究以AI腦出血判讀系統為主題，相較以往，諸多與AI腦出血判讀系統的相關研究，較少去探討醫療人員使用AI腦出血判讀系統的接受度。本研究主要探討急診醫師使用AI腦出血判讀系統的接受度，以科技接受模式（TAM）為主要架構。
研究方法
本研究為探討台灣急診醫師對 AI 腦出血判讀系統的接受度，了解目前台灣急診醫師對於 AI 腦出血判讀系統的使用意願及認知情形，將參考Davis(1989)提出的Technology Acceptance Model (TAM) 模式，綜合參考國內外文獻後，自行設計問卷一份，分為紙本與線上問卷，紙本問卷發放至各醫院單位，線上問卷則透過Surveycake、google表單設計，在完成問卷調查後進行分析與探討，主要是想了解台灣急診醫師對於 AI 腦出血判讀系統的了解與接受程度。
研究結果
本研究共有83位受試者，皆為使用過AI腦出血判讀系統之醫療人員，其中男性比例佔85.5%，女性佔14.5%；年齡大多分布在36~50歲(44.6%)，35歲以下佔34.9%，51歲以上佔20.5%；教育程度為醫學士或學士後醫較多；大多數的人不曾擔任過主管(80.7%)；超過一半的受試者在醫學中心工作(88.0%)，所屬健保分區以高屏為最多(73.5%)。透過皮爾森相關分析，科技接受模式各個構面具有顯著正相關性，代表每個構面皆有中高度的相關。多元線性迴歸分析各構面有無正向（或負向）影響，知覺易用性β值=0.102，P=0.305；知覺有用性β值=0.415，P<0.001；社會影響力β值=0.362，P=0.002；R2=0.650。

結論與建議
人工智慧在近年來已普遍融入於醫療之中，有望對醫學的各個領域產生許多影響，只要設計得當便能成為醫療界有利的輔助，並帶來許多好處；由研究結果可知各構面之平均數的高低，受試者普遍對於腦出血判讀系統接受度高，並認為醫院應支持此系統。在知覺易用性與知覺有用性上平均數較低，可在這兩個構面上多加強，若能提高系統的知覺易用性與知覺有用性，便能有效提升接受度。唯有51歲以上受試者仍較少，若要推廣人工智慧可從年紀較長之使用者進行教育訓練與宣導，增加其使用意願，並為即將到來的科技新時代做出充足的準備。

Background
With the progress of medical science and technology, artificial intelligence has been created and integrated. According to the statistics of the Ministry of Health and Welfare of Taiwan, cerebrovascular diseases occupy the fourth place among the top ten causes of death in Taiwan in 2019, ranking the same in the past five years. Therefore, it can be seen that cerebrovascular diseases have always affected the health of Taiwanese people. Therefore, the subject of this study is the AI cerebral hemorrhage interpretation system. Compared with previous studies, there are many related studies on the AI cerebral hemorrhage interpretation system, but few studies have discussed the acceptance of the AI cerebral hemorrhage interpretation system used by medical personnel. This study explores the acceptance of the AI cerebral hemorrhage interpretation system used by emergency physicians, using the technology acceptance model (TAM) as the main framework.

Methods
The purpose of this study is to explore the acceptance of the AI cerebral hemorrhage interpretation system by emergency physicians in Taiwan and understand the willingness and cognition of emergency physicians in Taiwan to use the AI cerebral hemorrhage interpretation system. After referring to the Technology Acceptance Model Davis (1989) and comprehensively referring to domestic and foreign literature, a questionnaire was designed, divided into paper and online questionnaires. The paper questionnaire was sent to each hospital, and the online questionnaire was designed through SurveyCake and Google form. After the questionnaire was completed, the analysis and discussion were conducted, mainly to understand and accept the AI cerebral hemorrhage interpretation system by emergency physicians in Taiwan.

Results
There are 83 subjects in this study; all of them were medical personnel who had used the AI cerebral hemorrhage detection system, among which 85.5% are male, and 14.5% are female. Most of them were from 36 to 50 years old (44.6%), 34.9% were below 35 years old, and 20.5% were over 51 years old. More doctors with Bachelor of Medicine or Bachelor of Medicine education; The majority had not held a supervisory position (80.7%); More than half of the subjects worked in medical centers (88.0%), Kaoping Divisions had the largest number of Divisions (73.5%). According to Pearson correlation analysis, each aspect of the technology acceptance model has a significant positive correlation, which means that each aspect has a medium to high correlation. Multiple linear regression analysis showed that the perceived ease of use β value was 0.102, P=0.305. β value of perceptual usefulness =0.415, P<0.001; β value of social influence =0.362, P=0.002; R2= 0.650.

Conclusions
In recent years, artificial intelligence has been widely integrated into medical treatment, which is expected to exert much influence on various fields of medicine. As long as it is properly designed, it can become a favorable auxiliary and bring many benefits to the medical community. According to the study results, the average of each dimension can be evaluated, and the subjects generally accepted the cerebral hemorrhage interpretation system and thought that the hospital should support this system. The average value of perceived ease of use and usefulness is low, and more enhancement can be made on these two dimensions. If the perceived ease of use and usefulness of the system can be improved, the acceptability can be effectively improved. Only subjects over 51 years old are still relatively small. To promote artificial intelligence, we should educate older users to increase their willingness to use, and make adequate preparations for the coming new era of technology.

目 錄
論文審定書 ........................................................................................i
摘 要 ................................................................................................... ii
Abstract .............................................................................................. iv
圖 次 .................................................................................................. ix
表 次 ................................................................................................. x
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究問題 2
第三節 研究目的 2
第四節 研究步驟 2
第五節 研究價值 4
第二章 文獻探討 5
第一節 人工智慧相關研究回顧 5
第二節 科技接受模式 6
第三節 AI腦出血判讀系統 8
第四節 核心文獻整理 9
第五節 文獻探討小節 10
第三章 研究方法 11
第一節 研究架構與假說 11
第二節 研究對象 15
第三節 問卷設計 15
第四節 問卷前測結果分析與問卷信效度 20
第五節 問卷統計分析與數據處理 23
第四章 研究結果 25
第一節 描述性統計分析 25
第二節 各構面之平均數與標準差 27
第三節 人口學特徵與各構面之差異性 29
第四節 皮爾森相關分析 37
第五節 多元線性回歸分析 38
第 五 章 討論與建議 39
第一節 討論 39
第二節 研究限制 41
第三節 倫理審查(IRB) 41
第四節 未來研究方向與建議 41
第六章 結論 42
第一節 結論 42
第二節 研究貢獻 42
參考文獻 44
附錄一 正式問卷 48

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