01 Project Synopsis
₹49
One-time Payment
- PDF & Word Formats
- Project Introduction & Objectives
- Problem Statement & Methodology
- System Architecture Diagram included
- Structured for Review & Customization
B.E. Project Report
B.E. Electronic Health Recognition Summarization Final Year Flask Project Report
Get structured B.E. Electronic Health Recognition Summarization Final Year Flask Project Report Final Year Project Report and Documentation with project objectives, methodology, system design, diagrams, implementation details, testing and complete project explanations. Suitable as a learning, documentation and project-presentation resource for students working on related final year projects.
Need a customized report? Chat on WhatsAppChoose the Report Package That Fits You Best
Simple pricing. Instant access. Every package includes PDF & Word format.
02 Detailed Project Report
₹99
One-time Payment
- PDF & Word Formats
- Structured Project Chapters
- UML / DFD / Technical Diagrams
- Methodology, Implementation & Testing
- Structured chapters & technical diagrams
03 Customized Project Report
₹149
One-time Payment
- PDF & Word both included
- Customized to your college documentation format
- Project-specific customized documentation
- Structured chapters & technical diagrams
- Delivery within 24-48 hours
04 Customized Plagiarism-Free Report
₹299
One-time Payment
- PDF & Word both included
- Plagiarism-free project content
- Original & project-specific writing
- Clear, natural & readable documentation
- Delivery within 24-48 hours
-
—
Abstract
-
—
Table of Content
-
01
Introduction
-
02
Problem Statement
-
03
Existing System
-
04
Proposed System
-
05
Objectives
-
06
System Architecture
-
07
Major Functional Modules
-
08
Hardware Requirements
-
09
Software Requirements
-
10
Future Enhancement
-
11
Conclusion
-
12
References
-
—
Abstract
-
—
Table of Content
-
01
Chapter 1 — Introduction
- 1.1 Background of the Project
- 1.2 Problem Statement
- 1.3 Objectives of the System
- 1.4 Scope of the Project
- 1.5 Existing System Overview
- 1.6 Proposed System Overview
- 1.7 Technologies Used
- 1.8 Overview
- 1.9 Limitations
- 1.10 Advantages
- 1.11 Disadvantages
-
02
Chapter 2 — Literature Review / System Study
- 2.1 Introduction
- 2.2 Review of Similar Systems
- 2.3 Comparative Analysis
- 2.4 Software Development Models
-
03
Chapter 3 — System Analysis
- 3.1 Introduction
- 3.2 Functional Requirements
- 3.3 Non-Functional Requirements
- 3.4 User Requirements
- 3.5 Feasibility Study
- 3.5.1 Technical Feasibility
- 3.5.2 Economic Feasibility
- 3.5.3 Operational Feasibility
- 3.6 System Architecture
- 3.7 Data Flow Diagram (Level 0)
- 3.8 Data Flow Diagram (Level 1)
- 3.9 Data Flow Diagram (Level 2)
-
04
Chapter 4 — System Design
- 4.1 Introduction
- 4.2 Use Case Diagram
- 4.3 Class Diagram
- 4.4 Sequence Diagram
- 4.5 Activity Diagram
- 4.6 ER Diagram
- 4.7 Database Schema
- 4.8 Table Structures
-
05
Chapter 5 — System Implementation
- 5.1 Introduction
- 5.2 Development Environment
- 5.3 Tools and Technologies Used
- 5.4 Hardware Requirements
- 5.5 Software Requirements
- 5.6 Module-wise Implementation
-
06
Chapter 6 — Testing
- 6.1 Introduction
- 6.2 Testing Strategy
- 6.3 Unit Testing
- 6.4 Integration Testing
- 6.5 System Testing
- 6.6 Test Cases
- 6.7 Bug Reports
-
07
Chapter 7 — Results and Discussion
- All screenshots
-
08
Chapter 8 — Conclusion and Future Enhancements
- 8.1 Conclusion
- 8.2 Future Enhancements
-
09
Chapter 9 — References
Project's Overview
MedSynapse EHR is a final year project built with Python Flask for students who want a healthcare-focused web application with document processing and clinical summarization features. This final year project allows users to add patients, upload PDF or TXT electronic health records, extract text, generate structured 8-section summaries, compare extracted content with generated sections, edit the final narrative, and download summary reports as PDF. The admin side of this final year project includes users, patients, EHR documents, summaries, medical categories, terms, diseases, medicines, reports, and branding settings. The system works with a heuristic summarizer by default and also supports optional Hugging Face Flan-T5 fine-tuning for advanced experimentation. MedSynapse EHR is suitable for a final year major project in Flask, healthcare software, NLP, or AI-assisted clinical documentation.
Login Credentials
Administrator
- Email:
[email protected] - Password:
Admin@123
Sample End Users
- Email:
[email protected] - Password:
User@123 - Email:
[email protected] - Password:
User@123
Related & Popular Reports
View all
Agricultural Monitoring and Crop Prediction System with Machine Learning
- Report
- Synopsis
- Diagrams
- Admin dashboard for this final year project with system-wide metrics
- User account creation, viewing, editing, blocking/unblocking, and deletion
- Patient listing, creation, owner assignment, detail view, editing, and deletion
- EHR document listing, full-text reading, metadata viewing, and deletion
- Summary listing, reading, editing, saved-flag management, and deletion
- Medical category CRUD with term counts
- Medical term CRUD with optional category link
- Disease CRUD with unique names
- Medicine CRUD with dosage and usage text
- Brand/system settings with product name, contact email, address, description, and logo upload
- Aggregate reports for users, patients, EHR files, summaries, and taxonomy
- Admin password change and logout
- End-user registration and login in this final year project
- Dashboard with totals, recent summaries, workflow guidance, and quick actions
- Patient add, list, edit, and delete features
- Upload EHR files in PDF or TXT format
- PDF text extraction using
pypdf - TXT file reading as UTF-8
- Re-extraction support from EHR detail page
- 8-section clinical summary generation
- Side-by-side original extracted text and generated summary comparison
- Editable narrative summary
- Draft update and final summary save
- PDF report download
- Summary history with open, edit, download, and delete options
- Search by patient name, external ID, condition hint, or summary fields
- Profile update and password change
- Logout functionality
- Public landing and authentication pages included in this final year project
- Role-based user and administrator consoles
- SQLite default database with configurable
DATABASE_URL - CSRF protection using Flask-WTF
- Password hashing and session login support
- 16 MB upload limit
- Heuristic summarization mode that works without GPU
- Optional Hugging Face Flan-T5 summarization mode
- Optional ML training scripts and JSONL export flow
- PDF summary generation using
fpdf2 - Upload and branding folders created at runtime
- Suitable for final year project demo, viva, source code review, and report preparation
- Healthcare disclaimer required before real use
- Open the final year project folder in a terminal.
- Create and activate a virtual environment:
python -m venv .venv
Windows:.venv\Scripts\activate
Linux/macOS:source .venv/bin/activate - Install the web app dependencies:
pip install -r requirements.txt - Optional: copy environment file and configure values:
Windows:copy env.example .env
Linux/macOS:cp env.example .env - Seed demo data and default accounts:
python seed_data.py - Start the final year Flask project server:
python run.py - Open the application at:
http://127.0.0.1:5000/ - Optional ML training setup:
pip install -r requirements-ml.txt
Then export training data and fine-tune Flan-T5 only if you have enough quality examples and suitable hardware.
README Included
Setup Support Available
Administrator
- Email:
[email protected] - Password:
Admin@123
Sample End Users
- Email:
[email protected] - Password:
User@123 - Email:
[email protected] - Password:
User@123