医疗器械显示屏的智能扫描可以与mHealth应用程序集成
Pedro Lobo1,2, João L Vilaça1,2, Helena Torres1,2,3,4,5
12AI, School of Technology, IPCA, Barcelos, Portugal.
Heliyon
|June 22, 2023
概括
这项研究引入了一种智能扫描系统,用于从医疗设备屏幕中提取数据,改善健康监测. 该系统使用对象检测模型来识别值,旨在与mHealth应用程序无集成.
科学领域:
- 生物医学工程 生物医学工程
- 计算机科学 计算机科学
- 人工智能的人工智能
背景情况:
- 每日对生理参数的监测对于健康管理至关重要.
- 医疗器械与智能手机的互连性促进了健康数据的收集.
- 目前对于智能手机连接医疗设备的制造商特定应用程序存在限制.
研究的目的:
- 为简化医疗器械数据收集提出一个智能扫描系统.
- 开发一种能够识别并可选集各种医疗器械屏幕数据的系统.
- 通过开放的协议使数据与集中数据库集成成为可能.
主要方法:
- 创建了一个由1614个医疗器械图像组成的数据集.
- 训练有素的对象检测算法 (yolov3,SSD 320x320,SSD 640x640) 可以检测数字和缩写/单位.
- 采用卷积神经网络 (CNN) 和密度空间聚类来进行对象识别和分组.
主要成果:
- 15个标签的SSD 640x640型号展示了最有前途的性能.
- 对象检测算法成功识别了医疗器械显示器上的数字和测量单位.
- 开发了一种策略,以有效地分组识别的数字.
结论:
- 开发的系统显示了有效提取医疗数据的潜力.
- 未来的工作包括将系统转换为移动环境,用于移动健康集成.
- 这一进步可以简化数据输入到移动健康应用程序.
关键词:
人工智能 (AI) 是一种人工智能.消费者健康信息 消费者健康信息数据汇总,数据聚合.数据收集 数据收集医疗器械 医疗器械 医疗器械这是OCR (光学字符识别).在线医疗服务 (e-health)移动健康 移动健康 移动健康 移动健康更多相关视频
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