國立虎尾科技大學 |

The Adoption of AI Technological Innovation in Hospital Systems: The Case of Computer-Assisted Diagnosis Adoption and Diffusion.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	The Adoption of AI Technological Innovation in Hospital Systems: The Case of Computer-Assisted Diagnosis Adoption and Diffusion./
作者:	Scrivner, James H., Jr.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2024,
面頁冊數:	145 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-07, Section: B.
Contained By:	Dissertations Abstracts International85-07B.
標題:	Medical imaging. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30990788
ISBN:	9798381435474

The Adoption of AI Technological Innovation in Hospital Systems: The Case of Computer-Assisted Diagnosis Adoption and Diffusion.
Scrivner, James H., Jr.

The Adoption of AI Technological Innovation in Hospital Systems: The Case of Computer-Assisted Diagnosis Adoption and Diffusion. - Ann Arbor : ProQuest Dissertations & Theses, 2024 - 145 p.

Source: Dissertations Abstracts International, Volume: 85-07, Section: B.

Thesis (Ph.D.)--Sullivan University, 2024.

This item must not be sold to any third party vendors.

Missed cancer diagnosis in medical imaging associated with human error is often due to case volume, human fatigue, incorrect patient positioning, and anatomical variation which can lead to delays in treatments and adverse patient events. In the last decade, there has been an increase in innovative technology development, particularly artificial intelligence to improve the performance, precision, and efficiency of early cancer detection and diagnosis. Among those technological innovations is computer-aided diagnosis (CAD) for lung which when optimized can support radiologists in the early detection of pulmonary lung nodules leading to improved diagnosis and patient survival. However, when the relationship between technology and end-user is less than optimal, the usability of such technology can be affected. Research on technology acceptance and diffusion has traditionally been studied from an individual perspective using the Technology Acceptance Model (TAM) framework. This research will extend the diffusion framework by proposing an integrated model the Expanded Technology Adoption Model (ETAM) based on the theories of: 1) Unified Theory of Acceptance and Use of Technology (UTAUT) and 2) Diffusion of Technology (DOI) to evaluate the interaction of CAD and the end-user. This integrated model will evaluate the interaction of CAD and the end-user by incorporating structural equation modeling (SEM) to gain a better understanding of the relationships between the latent structures of the independent variables (trust, accuracy, and efficiency) and the dependent variables (adoption and diffusion) from a behavioral, psychological, and social perspective.

ISBN: 9798381435474Subjects--Topical Terms:

1180167
Medical imaging.
Subjects--Index Terms:

Computer-aided diagnosis

The Adoption of AI Technological Innovation in Hospital Systems: The Case of Computer-Assisted Diagnosis Adoption and Diffusion.
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506 $a This item must not be sold to any third party vendors.
520 $a Missed cancer diagnosis in medical imaging associated with human error is often due to case volume, human fatigue, incorrect patient positioning, and anatomical variation which can lead to delays in treatments and adverse patient events. In the last decade, there has been an increase in innovative technology development, particularly artificial intelligence to improve the performance, precision, and efficiency of early cancer detection and diagnosis. Among those technological innovations is computer-aided diagnosis (CAD) for lung which when optimized can support radiologists in the early detection of pulmonary lung nodules leading to improved diagnosis and patient survival. However, when the relationship between technology and end-user is less than optimal, the usability of such technology can be affected. Research on technology acceptance and diffusion has traditionally been studied from an individual perspective using the Technology Acceptance Model (TAM) framework. This research will extend the diffusion framework by proposing an integrated model the Expanded Technology Adoption Model (ETAM) based on the theories of: 1) Unified Theory of Acceptance and Use of Technology (UTAUT) and 2) Diffusion of Technology (DOI) to evaluate the interaction of CAD and the end-user. This integrated model will evaluate the interaction of CAD and the end-user by incorporating structural equation modeling (SEM) to gain a better understanding of the relationships between the latent structures of the independent variables (trust, accuracy, and efficiency) and the dependent variables (adoption and diffusion) from a behavioral, psychological, and social perspective.
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