提高眼科医生基于人工智能技术的临床决策效率和准确性
Yingxuan Guo1, Changke Huang1, Yaying Sheng1
1School of Ophthalmology and Optometry, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
BMC medical informatics and decision making
|July 9, 2024
概括
一个新的智能决策支持平台显著提高了初级医生对眼底部疾病的诊断准确度. 这种人工智能工具有助于弥合经验差距,确保更快,更精确的患者护理.
科学领域:
- 眼科医生 眼科 眼科
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 全球日益老龄化增加了眼底疾病的流行率.
- 由于医生与患者的比例,中国在早期诊断和治疗方面面临挑战.
- 提高初级医生的诊断技能对于预防视力障碍至关重要.
研究的目的:
- 利用电子医疗记录数据开发一个人工智能支持的决策支持平台.
- 协助初级医生准确和快速诊断眼底部疾病.
- 加速初级医生的专业发展,提高患者治疗的及时性.
主要方法:
- 对比了八个中国命名实体识别 (NER) 模型,选择软词典-手套-Word2vec (F1得分:93.02%).
- 使用NER提取EMR数据以创建特征变量.
- 使用XGBoost算法开发了一个智能决策支持平台.
主要成果:
- 该平台显著提高了所有医生的诊断效率和准确性 (P <0.05).
- 新手和经验丰富的医生之间的诊断绩效差距大幅缩小.
- 与经验丰富的医生相比,初级医生表现出更明显的改善.
结论:
- 人工智能平台有效地提高了初级医生对眼底部疾病的诊断能力.
- 该研究强调了该平台在优化临床诊断和治疗途径方面的潜力.
- 这种人工智能驱动的方法有助于减少诊断错误并改善患者的治疗结果.
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