Natural Language Processing and Automated Speech Recognition to Identify Older Adults with Cognitive Impairment Supplement

自然语言处理和自动语音识别可识别患有认知障碍的老年人补充剂

• 批准号: 10599624
• 负责人: Jalayne J Arias
• 金额: $ 34.8万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-15 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10599624
• 关键词: Address; Adoption; Artificial Intelligence; Bioethics; Clinical; Collaborations; Computers; Data; Data Collection; Development; Disclosure; Elderly; Ethical Issues; Ethics; Focus Groups; Health Technology; Healthcare; Impaired cognition; Informed Consent; Interview; Knowledge; Literature; Methods; Minority Groups; Natural Language Processing; Outpatients; Paper; Parents; Patient Care; Patients; Perception; Physicians; Primary Health Care; Publications; Qualitative Methods; Research; Research Ethics; Scientist; Techniques; Underrepresented Minority; Underrepresented Populations; Work; automated speech recognition; clinical care; health care settings; health disparity; insight; minority health; minority patient; multidisciplinary; screening; stakeholder perspectives; tool

Existing ethical frameworks for the study and or development of artificial intelligence (AI) technology for health care applications are largely conceptual, lacking critical insights from patients and clinicians, including patients from racial and ethic minority groups. Building on the Parent Study (R01 AG066471), which is developing automated techniques for cognitive impairment screening in primary care, we plan to use qualitative methods to collect perspectives from diverse patient groups, and from physicians, and integrate these data with concepts and data from the literature on ethical challenges of AI research in healthcare. While the Parent Study is specific to cognitive impairment screening, we anticipate that the activities of this project will generate a framework with broader applications. The proposed project harnesses a collaboration of a multi-disciplinary team of clinicians, computer scientists, experts in minority health, and bioethics. The specific aims are (1) to identify and characterize the perceptions and concerns of patients, including those from underrepresented minority groups, and clinicians about AI methods for automated screening for cognitive impairment in outpatient clinical settings; and (2) to integrate this knowledge with existing ethical frameworks of AI research and healthcare screening to develop a more comprehensive ethical framework for the ethical conduct of AI research in healthcare settings. We will first integrate several established ethical frameworks on AI research and healthcare screening and use the resultant preliminary framework to inform qualitative data collection. Next, we will conduct qualitative interviews with patients from diverse backgrounds to understand their perspectives on automated screening and AI research in clinical care (e.g., informed consent, disclosure of results), and focus groups with clinicians for their views on ethical challenges that could hinder adoption. In parallel, we will conduct a PRISMA-Scoping review to identify additional relevant frameworks and research, and interactively refine our qualitative data collection. Finally, we will integrate the qualitative data with concepts from existing literature and frameworks to establish a more comprehensive and inclusive framework than those currently in publication. In this fashion, the work will inform the ethical conduct of research on AI-driven automated cognitive impairment screening and AI research for other conditions. This supplement is responsive to NOT-OD-22-065 by supporting a new collaboration on AI research ethics and developing generalizable methods of exploring and addressing ethical impacts throughout the AI research cycle, specifically through advancing AI research ethical frameworks.

研究和/或开发健康人工智能 (AI) 技术的现有伦理框架 护理应用程序很大程度上是概念性的，缺乏患者和临床医生（包括患者）的批判性见解 来自种族和族裔少数群体。以家长研究 (R01 AG066471) 为基础，该研究正在开发中 初级保健中认知障碍筛查的自动化技术，我们计划使用定性方法 收集不同患者群体和医生的观点，并将这些数据与概念相结合 以及有关医疗保健领域人工智能研究的伦理挑战的文献数据。虽然家长研究是具体的 对于认知障碍筛查，我们预计该项目的活动将生成一个框架 更广泛的应用。拟议的项目利用了多学科临床医生团队的合作， 计算机科学家、少数民族健康和生物伦理学专家。具体目标是 (1) 确定和 描述患者的看法和担忧，包括来自代表性不足的少数群体的患者， 和临床医生了解门诊临床环境中自动筛查认知障碍的人工智能方法； (2) 将这些知识与人工智能研究和医疗保健筛查的现有道德框架相结合，以 为医疗保健环境中人工智能研究的道德行为制定更全面的道德框架。 我们将首先整合几个已建立的人工智能研究和医疗保健筛查和使用的道德框架 由此产生的初步框架为定性数据收集提供信息。接下来我们将进行定性 采访来自不​​同背景的患者，了解他们对自动筛查的看法 临床护理中的人工智能研究（例如知情同意、结果披露）以及临床医生的焦点小组 他们对可能阻碍采用的道德挑战的看法。与此同时，我们将进行 PRISMA-Scoping 审查以确定其他相关框架和研究，并交互式地完善我们的定性数据 收藏。最后，我们将定性数据与现有文献和框架中的概念相结合 建立比目前出版的框架更全面、更具包容性的框架。以这种方式， 这项工作将为人工智能驱动的自动认知障碍筛查和人工智能研究的道德行为提供信息 研究其他条件。该补充通过支持新的 NOT-OD-22-065 来响应 人工智能研究伦理方面的合作，并开发探索和解决伦理问题的通用方法 影响整个人工智能研究周期，特别是通过推进人工智能研究伦理框架。