摘要
目的阐述人工智能在医疗护理领域的应用现状和存在问题,推动人工智能以合乎道德且高效的方式融入医疗护理领域,以推动智能技术在医疗护理领域的深度融合和健康发展。方法结合护理领域现状,全面调研人工智能在医疗护理领域的具体应用,分析人工智能带来的问题和挑战,并提出相应的优化建议。结果人工智能在医疗护理应用中存在数据安全、算法歧视、护患关系异化、责任归属模糊等问题,制约医疗护理智能化发展。社会和医疗组织可采取相应的对策,包括制定法律法规、加强技术创新、加强护士职业教育等,提高算法公平,优化人工智能医疗护理服务。结论为了充分发挥人工智能在医疗护理领域的优势并解决其带来的问题,人们需要综合运用法律制度、技术创新和伦理规范等手段,为患者提供更高质量的人工智能医疗护理服务。
Objective To describe the status quo and problems of the application of AI in medical care,and to facilitate the ethical and effective integration of Artificial intelligence(AI)into medical nursing,so as to promote the deep integration and healthy development of intelligent technology in this field.Methods On the basis of the current situation of the nursing field,we investigated the specific application of AI in medical nursing,analyzed the problems and challenges brought by AI,and put forward corresponding optimization suggestions.Results Artificial Intelligence application in the field of medical nursing brought about problems such as data security,algorithmic discrimination,alienation of the nurse-patient relationship,and ambiguous attribution of responsibility,thus restricting the intelligent development of medical nursing.The social and medical organizations could take corresponding countermeasures,including formulating laws and regulations,strengthening technological innovation,and enhancing nurses’professional education,to improve algorithmic fairness and optimize AI medical nursing services.Conclusions In order to fully utilize AI’s strengths in medical nursing and solve the related problems,it is necessary to make a comprehensive use of the legal system,technological innovation,and ethical norms to provide patients with higher-quality AI medical nursing services.
作者
刘漫
沈鹏熠
张茹梦
LIU Man;SHEN Pengyi;ZHANG Rumeng(Hospital of Jiangxi University of Finance and Economics,Nanchang,Jiangxi 330013,China;不详)
出处
《中国农村卫生事业管理》
2025年第3期177-182,共6页
Chinese Rural Health Service Administration
基金
国家自然科学基金项目(72262016)
江西省高等学校教学改革研究重点项目(JXJG-23-4-2)。
关键词
人工智能
人工智能护理
护患关系
风险挑战
应对策略
Artificial Intelligence
AI nursing
Nurse-patient relationship
Risks and challenges
Countermeasure
