儿童人工智能挑战对人工智能教育和课程开发的影响
Dana Alkhulaifat1, Patricia Rafful1, Vahid Khalkhali2
1Department of Pediatric Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
小儿放射学需要一个专门的人工智能 (AI) 课程. 这种人工智能教育必须解决独特的儿科成像挑战和有效临床实施的伦理考虑.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 医学教育 医学教育
背景情况:
- 现有的放射学人工智能 (AI) 课程缺乏针对儿科特定应用的重点.
- 儿科放射学实践模式与成人放射学有很大的不同,这影响了AI模型的概括性.
研究的目的:
- 突出在儿科放射学上需要一个量身定制的人工智能课程.
- 确定在儿科成像中开发和实施AI的关键考虑因素.
主要方法:
- 审查当前的AI放射学教育产品.
- 分析与AI相关的儿科放射学实践的独特方面.
- 识别儿科人工智能研究和临床应用中的挑战.
主要成果:
- 主要的放射学学会提供通用AI培训,但没有专门针对儿科的内容.
- 儿童人工智能教育必须考虑到成像方式,获取参数,辐射剂量,儿童发育和疾病患病率的差异.
- 儿科人工智能的挑战包括数据治理,伦理考虑和临床实施.
结论:
- 为儿童放射学制定专门的AI课程对于该领域的进步至关重要.
- 课程必须整合儿科特定的挑战,人工智能模型评估和道德准则.
- 解决这些问题将提高放射科医生在将人工智能应用于儿科患者方面的能力.
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