Reflections on the Clinical Acceptance of Artificial Intelligence

Assessing the Acceptance of Clinical Decision Support Tools using an Integrated Technology Acceptance Model

With the medical development in recent decades, the multiplicity of different diseases, and an increased number of patients, the use of an advanced healthcare information technology (HIT) such as a clinical decision support system (CDSS) has been of necessary to help general practitioners (GPs). CDSS may fail due to the failure to understand the factors influencing the GP's acceptance of CDSS. Identifying factors that promote acceptance of CDSS can be a vital aspect for its successful implementation. This study seeks to identify factors that influence the acceptance of CDSS in Saudi Arabia by …

Clinical acceptance of software based on artificial intelligence technologies (radiology)

Aim: provide a methodological framework for the process of clinical tests, clinical acceptance, and scientific assessment of algorithms and software based on the artificial intelligence (AI) technologies. Clinical tests are considered as a preparation stage for the software registration as a medical product. The authors propose approaches to evaluate accuracy and efficiency of the AI algorithms for radiology.

An Integration of UTAUT and Task-Technology Fit Frameworks for Assessing the Acceptance of Clinical Decision Support Systems in the Context of a Developing Country

This paper is to create a basis of theoretical contribution for a new PhD thesis in the area of Clinical Decision Support Systems (CDSS) acceptance. Over the past three years, we conducted qualitative research into three distinctive phases to develop an extended Task-Technology Fit (TTF) Framework. These phases are for initiating requirement generation of the framework, discovering the factors of the framework through perspectives, and evaluating the new proposed framework. The new condition is related to developing country in which various sectors such as healthcare is mostly under attention.…

面向具备文化胜任力的临床沟通的聊天机器人协同设计：经验与反思

Co-Designing a Chatbot for Culturally Competent Clinical Communication: Experience and Reflections

本研究设计了基于ACT文化胜任力模型的AI聊天机器人用于医学生跨文化临床沟通培训，英国医学院试点显示其可辅助学生反思共情等能力，但存在缺乏非语言线索等局限。

CareMirror：将照护者福祉引入痴呆症照护生态系统

CareMirror: Bringing Caregiver Wellbeing into the Dementia Care Ecosystem

本研究提出CareMirror生态系统，通过访谈14名照护者，探索支持其福祉的纵向反思与临床共享设计，强调AI辅助但不替代人类判断，为主动临床相连的照护者支持提供设计考量。

MedSimAI：通过模拟和形成性反馈提升医学教育中的刻意练习

MedSimAI: Simulation and Formative Feedback Generation to Enhance Deliberate Practice in Medical Education

MedSimAI通过模拟和形成性反馈提升医学教育中的刻意练习，通过AI生成临床互动并提供自动评估，提高病史采集和沟通技能。