可互操作的电子健康记录 (EHR) 应用程序的设计,用于通过扩大深度学习技术来使用决策支持系统早期检测肺部疾病
Jagadamba G1, Shashidhar R2, Vinayakumar Ravi3
1Department of Information Science and Engineering, Siddaganaga Institute of Technology, Tumakuru, Karnataka- 57210, India.
The open respiratory medicine journal
|August 12, 2024
概括
这项研究开发了电子健康记录 (EHR) 的Android应用程序,以及用于早期肺癌检测的深度学习决策支持系统,达到93%的准确性. 该系统有助于有效访问患者数据和识别疾病.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 在瘤学瘤学.
背景情况:
- 电子健康记录 (EHR) 提供全面的数字患者数据,增强医疗保健决策和治疗.
- 电子健康数据提供了数据分析的机会,以提高效率和识别健康问题.
研究的目的:
- 实施可互操作的EHR系统,并配备用于早期肺癌识别的决策支持系统.
- 开发一个Android应用程序用于EHR管理和基于深度学习的决策支持系统,用于早期发现疾病.
主要方法:
- 开发了一个Android应用程序来收集和管理患者的EHR数据.
- 通过使用深度学习对316名患者 (年龄在40-70岁之间) 的图像创建了一个决策支持系统,用于肺癌预测.
- 数据被分为80:20用于培训和测试,并对大细胞癌,腺癌和状细胞癌进行手动分类.
主要成果:
- 电子健康记录系统证明了数据收集和更新的互操作性.
- 深度学习模型预测了80:20的训练/测试比率的肺癌类型 (大细胞癌,腺癌,状细胞癌).
- 与其他类型相比,大细胞癌的预测准确性较低,与性别和吸烟习惯有相关性.
结论:
- 通过Android应用程序访问的安全,可互操作的EHR系统可以改善患者数据管理.
- 深度学习决策支持系统成功实现了早期肺癌检测,准确率为93%.
- 未来的工作包括整合EHR数据,以便早期检测更广泛的疾病.
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