About this Research Topic
The goal of this Research Topic is to understand the implications for designing and integrating clinical AI into healthcare settings from approaches that aim for human-centered AI. We are particularly curious about process challenges for implementation and gaps in sustainability for new AI being implemented. Target stakeholders include those that are designing and building AI technologies to address clinical challenges and consideration of how to help them better understand the difficulties in actual implementation in clinical settings. We seek to highlight the value of an empathic human-centered approach, which can facilitate better design, more appropriate implementation, and the likelihood of maintaining longer-term sustainable solutions.
Topics covered may include:
• Design research to inform Clinical AI (methods and case studies)
• Use of Implementation Science in Clinical AI practice integration
• Metrics for and measures of Clinical AI uptake, utility, and impact on users
• Case studies of Clinical AI Implementation
• Novel data sets and data capture methods to inform Clinical AI
• Empirical studies examining clinician and patient perceptions and risk-beliefs of Clinical AI
• Studies of legislative, professional, and regulatory frameworks for Clinical AI
• Medicolegal and ethical requirements and moral and professional responsibilities in an era of Clinical AI
Keywords: Human-Centered Design, AI, Clinical Applications, Implementation, Evaluation, Metrics, Human-AI Interaction
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.