用于诊断儿科尾炎的人工智能:系统性审查
Mariam Chekmeyan1, Shao-Hsien Liu1
1University of Massachusetts Morningside Graduate School of Biomedical Sciences, Worcester, MA, United States of America.
The American journal of emergency medicine
|March 6, 2025
概括
人工智能 (AI) 和机器学习 (ML) 在诊断儿科尾炎方面表现有前途,研究表明其准确性很高. 需要进一步的研究来将这些工具纳入临床实践.
科学领域:
- 儿科手术 儿科手术
- 医疗信息学 医疗信息学
- 诊断成像 诊断成像 诊断成像
背景情况:
- 急性尾炎是一种常见的儿科手术紧急情况,具有诊断挑战.
- 人工智能 (AI) 和机器学习 (ML) 为提高诊断准确性提供了潜在的解决方案.
- 本系统性审查评估了AI和ML在诊断急性儿科尾炎中的有效性.
结论:
- 人工智能和机器学习技术可以提高儿科尾炎诊断的准确性.
- 需要进一步的研究来解决采用障碍和现实世界的临床疗效.
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