Goh Wilson Wb, Chia Kendrick Ya, Cheung Max Fk, Kee Kalya M, Lwin May O, Schulz Peter J, Chen Minhu, Wu Kaichun, Ng Simon Sm, Lui Rashid, Ang Tiing Leong, Yeoh Khay Guan, Chiu Han-Mo, Wu Deng-Chyang, Sung Joseph Jy
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore, Singapore.
School of Biological Sciences, Nanyang Technological University, Singapore, Singapore.
JMIR AI. 2024 Mar 7;3:e50525. doi: 10.2196/50525.
The use of artificial intelligence (AI) can revolutionize health care, but this raises risk concerns. It is therefore crucial to understand how clinicians trust and accept AI technology. Gastroenterology, by its nature of being an image-based and intervention-heavy specialty, is an area where AI-assisted diagnosis and management can be applied extensively.
This study aimed to study how gastroenterologists or gastrointestinal surgeons accept and trust the use of AI in computer-aided detection (CADe), computer-aided characterization (CADx), and computer-aided intervention (CADi) of colorectal polyps in colonoscopy.
We conducted a web-based questionnaire from November 2022 to January 2023, involving 5 countries or areas in the Asia-Pacific region. The questionnaire included variables such as background and demography of users; intention to use AI, perceived risk; acceptance; and trust in AI-assisted detection, characterization, and intervention. We presented participants with 3 AI scenarios related to colonoscopy and the management of colorectal polyps. These scenarios reflect existing AI applications in colonoscopy, namely the detection of polyps (CADe), characterization of polyps (CADx), and AI-assisted polypectomy (CADi).
In total, 165 gastroenterologists and gastrointestinal surgeons responded to a web-based survey using the structured questionnaire designed by experts in medical communications. Participants had a mean age of 44 (SD 9.65) years, were mostly male (n=116, 70.3%), and mostly worked in publicly funded hospitals (n=110, 66.67%). Participants reported relatively high exposure to AI, with 111 (67.27%) reporting having used AI for clinical diagnosis or treatment of digestive diseases. Gastroenterologists are highly interested to use AI in diagnosis but show different levels of reservations in risk prediction and acceptance of AI. Most participants (n=112, 72.72%) also expressed interest to use AI in their future practice. CADe was accepted by 83.03% (n=137) of respondents, CADx was accepted by 78.79% (n=130), and CADi was accepted by 72.12% (n=119). CADe and CADx were trusted by 85.45% (n=141) of respondents and CADi was trusted by 72.12% (n=119). There were no application-specific differences in risk perceptions, but more experienced clinicians gave lesser risk ratings.
Gastroenterologists reported overall high acceptance and trust levels of using AI-assisted colonoscopy in the management of colorectal polyps. However, this level of trust depends on the application scenario. Moreover, the relationship among risk perception, acceptance, and trust in using AI in gastroenterology practice is not straightforward.
人工智能（AI）的应用可彻底改变医疗保健，但这引发了风险担忧。因此，了解临床医生如何信任和接受AI技术至关重要。胃肠病学因其基于图像且干预性强的特点，是AI辅助诊断和管理可广泛应用的领域。
本研究旨在探讨胃肠病学家或胃肠外科医生如何接受和信任在结肠镜检查中对结直肠息肉进行计算机辅助检测（CADe）、计算机辅助特征描述（CADx）和计算机辅助干预（CADi）时使用AI。
我们在2022年11月至2023年1月期间开展了一项基于网络的问卷调查，涉及亚太地区的5个国家或地区。问卷包括用户背景和人口统计学等变量；使用AI的意愿、感知风险；接受程度；以及对AI辅助检测、特征描述和干预的信任度。我们向参与者展示了3个与结肠镜检查和结直肠息肉管理相关的AI场景。这些场景反映了结肠镜检查中现有的AI应用，即息肉检测（CADe）、息肉特征描述（CADx）和AI辅助息肉切除术（CADi）。
共有165名胃肠病学家和胃肠外科医生对由医学交流专家设计的结构化问卷进行了基于网络的调查回复。参与者的平均年龄为44（标准差9.65）岁，大多数为男性（n = 116，70.3%），且大多在公立资助医院工作（n = 110，66.67%）。参与者报告称对AI的接触程度相对较高，111人（67.27%）报告曾使用AI进行消化系统疾病的临床诊断或治疗。胃肠病学家对在诊断中使用AI兴趣浓厚，但在风险预测和对AI的接受程度上表现出不同程度的保留意见。大多数参与者（n = 112，72.72%）也表示有兴趣在未来的实践中使用AI。83.03%（n = 137）的受访者接受CADe，78.79%（n = 130）的受访者接受CADx，72.12%（n = 119）的受访者接受CADi。85.45%（n = 141）的受访者信任CADe和CADx，72.12%（n = 119）的受访者信任CADi。在风险认知方面没有特定应用的差异，但经验更丰富的临床医生给出的风险评级较低。
胃肠病学家报告称在结直肠息肉管理中使用AI辅助结肠镜检查的总体接受度和信任度较高。然而，这种信任程度取决于应用场景。此外，在胃肠病学实践中，对使用AI的风险认知、接受程度和信任之间的关系并不简单。
