🏥 Dialysis Data Automation System | 透析数据自动化系统

🌍 English | 中文

Automated OCR and data entry solution for hemodialysis treatment records
透析治疗记录的自动 OCR 识别与数据录入自动化解决方案

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📖 English Documentation

📋 Table of Contents

• 🎯 Overview
• ✨ Key Features
• 🎬 Demo
• 💻 System Requirements
• 🚀 Quick Start
• 📖 User Guide
• 📁 Project Structure
• ⚙️ Configuration
• ❓ FAQ
• 🗺️ Roadmap
• 🤝 Contributing
• 📜 License
• 👨‍💻 Author

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🎯 Overview

An automated data entry system for hemodialysis units.
Uses OCR (Optical Character Recognition) to extract data from nursing records and dialysis machine screens, automatically filling them into the hospital's Origin System, reducing manual workload.

Background & Motivation

👩‍⚕️ Nurses manually enter large volumes of dialysis data daily
📄 Data from paper records and machine screens
⏰ Time-consuming, error-prone, repetitive
💡 Solution: OCR recognition + automation

Why This Project?

As a nurse learning programming, I created this tool to:

• 🎯 Solve real healthcare problems
• 🚀 Reduce colleagues’ workload
• 💻 Apply programming to nursing practice
• 🌟 Bridge technology and healthcare

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✨ Key Features

📸 OCR Recognition

✅ Nursing Record Recognition – Extracts date, BP, weight, dialysis parameters
✅ Machine Screen Recognition – Extracts hourly data (BP, VP, QB, QD, Pulse, UFR)
✅ High Accuracy – Powered by EasyOCR
✅ Smart Fault Tolerance – Flexible formats supported

🤖 Automated Data Entry

✅ Origin System Auto-login
✅ Auto-navigation to record page
✅ MRN-based patient search
✅ Auto-fill & save

💾 Data Management

✅ Import/Export JSON
✅ Validation & manual correction
✅ Operation logging

🌐 User Interface

✅ Bilingual (English + 中文)
✅ Intuitive 3-step workflow
✅ Real-time image preview
✅ Live logging

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🎬 Demo

┌─────────────────────────────────────────────────────────┐ │ 🏥 Dialysis Data Automation System │ │ Version 1.0.0 | For KLSCH Haemodialysis Unit │ ├─────────────────────────────────────────────────────────┤ │ Steps │ Image Preview │ Data Editor │ │ Step 1: Upload Photo │ [Preview] │ Basic Data │ │ Step 2: Extract Obs │ │ Hourly Obs │ │ Step 3: Auto Fill │ │ Complete! │ └─────────────────────────────────────────────────────────┘

Workflow:
📷 Photo → 🔍 OCR → ✏️ Verify → 🤖 Auto-fill → ✅ Done

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💻 System Requirements

Required

• Python 3.8+
• Windows 10/11 (Recommended) or Linux/Mac
• 4GB RAM, 500MB Disk
• Chrome Browser

Network

• Access to hospital Origin system
• Internet (for OCR model download)

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🚀 Quick Start

Method 1: One-Click Launch

git clone https://github.com/USAGI7878/dialysis-automation.git
cd dialysis-automation
start.bat
✅ Creates virtual env → Installs deps → Launches app

Method 2: Manual Installation
bash
Copy code
git clone https://github.com/USAGI7878/dialysis-automation.git
cd dialysis-automation
python -m venv venv
venv\Scripts\activate  # Windows
pip install -r requirements.txt
python main.py
📖 User Guide
Workflow
1️⃣ Upload nursing record → OCR
2️⃣ Verify/correct data
3️⃣ Upload machine screen → OCR hourly obs
4️⃣ Enter Origin credentials + MRN
5️⃣ Click “Auto Fill Data” → ✅ Done!

📁 Project Structure
pgsql
Copy code
dialysis-automation/
├── main.py
├── config.json
├── requirements.txt
├── start.bat
├── modules/
│   ├── ocr_module.py
│   ├── origin_automation.py
│   └── data_processor.py
├── data/
│   ├── exports/
│   └── temp/
├── logs/
│   └── automation.log
└── docs/
    └── screenshots/
⚙️ Configuration
json
Copy code
{
  "origin_url": "http://192.168.20.11:8080/EMR/main.jsp",
  "ocr_settings": {
    "use_gpu": false,
    "confidence_threshold": 0.5
  },
  "selenium_settings": {
    "headless": false,
    "implicit_wait": 10
  }
}
❓ FAQ
Q1: OCR not accurate?
✅ Use clear, well-lit photos
✅ Avoid glare, shadows
✅ Manually correct in “Data Editor”

Q2: Automation failed?
✅ Check network
✅ Verify credentials & MRN
✅ Check logs/automation.log

Q3: Use at home?
✅ OCR & data edit work offline
❌ Auto-fill requires hospital network

🗺️ Roadmap
✅ v1.0.0 – OCR, automation, bilingual UI
🚧 v1.1.0 – Accuracy, batch processing, reports
📅 v2.0.0 – Cloud sync, mobile app, AI validation

🤝 Contributing
Fork the repo

Create a branch

Commit & push

Submit a PR

📜 License
Licensed under the MIT License – see LICENSE file.

👨‍💻 Author
@USAGI7878 – Healthcare IT Nurse
📧 peggy8526123@gmail.com

<div align="center"> ⭐ If this project helps you, please give it a Star! Made with ❤️ by a nurse who codes. </div> </details>
<details> <summary><b>📖 中文文档</b></summary>
📋 目录
🎯 项目简介

✨ 核心功能

🎬 演示

💻 系统要求

🚀 快速开始

📖 使用指南

📁 项目结构

⚙️ 配置说明

❓ 常见问题

🗺️ 开发路线图

🤝 贡献指南

📜 许可证

👨‍💻 作者

🎯 项目简介
本系统为血液透析单位设计，利用 OCR 技术自动识别护理记录与透析机屏幕信息，自动填入医院 Origin 系统，显著减少人工输入。

✨ 核心功能
📸 OCR 识别
✅ 护理记录、透析机屏幕
✅ 高准确率 + 容错识别

🤖 自动化填表
✅ 登录、导航、自动录入

💾 数据管理
✅ 导入导出 JSON
✅ 手动校正、日志追踪

🌐 用户界面
✅ 中英双语、实时预览、操作简洁

🎬 演示
Copy code
📷 拍照 → 🔍 OCR识别 → ✏️ 验证 → 🤖 自动填表 → ✅ 完成
💻 系统要求
Python 3.8+

Windows 10/11 或 Linux/Mac

4GB RAM

Chrome 浏览器

可访问医院 Origin 系统

🚀 快速开始
bash
Copy code
git clone https://github.com/USAGI7878/dialysis-automation.git
cd dialysis-automation
start.bat
或手动安装：

bash
Copy code
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt
python main.py
📁 项目结构
详见英文部分。

⚙️ 配置说明
详见英文部分。

❓ 常见问题
OCR 识别不准确？
✅ 照片清晰、光线良好
✅ 避免反光、阴影
✅ 手动修正识别结果

自动化失败？
✅ 检查网络与登录信息
✅ 查看 logs/automation.log

🗺️ 开发路线图
✅ v1.0.0 – 基础功能
🚧 v1.1.0 – 批量处理与统计
📅 v2.0.0 – 云端同步与 AI 验证

👨‍💻 作者
@USAGI7878 – 医疗信息化护理师
📧 peggy8526123@gmail.com

<div align="center"> ⭐ 如果这个项目对你有帮助，请点亮 Star！ 由一位热爱编程的护理师 ❤️ 制作 </div>