人工智能驱动数据提取的机会和机会主义:以价值为中心的方法
Stephen Waite1, Matthew S Davenport2, Mark L Graber3
1Departments of Radiology and Internal Medicine, SUNY Downstate Medical Center, 450 Clarkson Ave, Brooklyn, NY 11203.
AJR. American journal of roentgenology
|September 18, 2024
概括
放射科医生的作用正在随着人工智能 (AI) 和大数据的发展而变化,转向从成像中提取全面信息,即使没有具体的临床问题. 这就需要新的工作流程和人工智能辅助预后和高价值护理的指南.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 放射科医生的传统角色包括回答特定的临床问题,以帮助治疗决策.
- 诸如人工智能 (AI),大数据分析和先进的成像技术等力量正在迅速改变放射学.
- 一个新的范式正在出现,放射科医生与人工智能一起,将从成像数据中提取最大的信息.
研究的目的:
- 在人工智能和大数据时代,审查放射科医生的不断变化的角色.
- 讨论人工智能辅助预测和信息提取所带来的挑战和机遇.
- 强调在现代放射学实践中确保高价值护理的重要性.
主要方法:
- 审查目前的趋势和在放射学的进步.
- 分析人工智能和大数据对放射学工作流程的影响.
- 讨论新兴的人工智能应用,包括从成像数据进行预测.
主要成果:
- 人工智能和大数据使放射科医生能够从成像中提取更多信息,预测长期结果 (人工智能辅助预后),并超越特定的临床问题.
- 整合人工智能需要简化工作流程,改进通信和强大的数据管理.
- 新出现的问题包括报销,责任和患者公平获得新技术.
结论:
- 放射科医生的角色正在扩大,超越传统的诊断解释,包括全面的数据提取和人工智能辅助预后.
- 解决与数据管理,报销,责任和访问有关的挑战对于有效整合人工智能至关重要.
- 确保高价值护理需要调整实践,并制定指导方针,以便在放射学中负责任地使用AI.
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