https://github.com/dvaser/mediary
This web application listens to the patient's story, analyzes possible diseases using AI, recommends necessary diagnostic tests, and finally generates a medical report based on the test results.
https://github.com/dvaser/mediary
ai artificial-intelligence django health healthcare healty machine-learning medical medicine patient python website
Last synced: 11 months ago
JSON representation
This web application listens to the patient's story, analyzes possible diseases using AI, recommends necessary diagnostic tests, and finally generates a medical report based on the test results.
- Host: GitHub
- URL: https://github.com/dvaser/mediary
- Owner: dvaser
- Created: 2025-06-28T09:36:52.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-07-27T19:46:12.000Z (11 months ago)
- Last Synced: 2025-07-27T21:36:50.620Z (11 months ago)
- Topics: ai, artificial-intelligence, django, health, healthcare, healty, machine-learning, medical, medicine, patient, python, website
- Language: Python
- Homepage:
- Size: 9.27 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Project: MEDIARY
## Project Purpose
> The aim is to automate processes such as diagnosing based on patient history, recommending tests, interpreting results, and providing personalized health assessments with the support of artificial intelligence.
>
> The project aims to provide clinical decision support for doctors, offer preliminary information to patients, and reduce the workload within the healthcare system.
>
> In the initial phase of the project, the data collection process has been focused on the field of Internal Medicine; therefore, diseases specific to this area will be prioritized for evaluation. In later stages, data will also be gathered from other medical specialties, aiming to obtain stronger insights into a broader range of health conditions.
## Team Details
> **[Click here to see team details](project/markdowns/team.md)**
## Sprint Details
> **[Click here to see the sprint-1 workouts](project/markdowns/sprint/sprint-1.md)**
>
> **[Click here to see the sprint-2 workouts](project/markdowns/sprint/sprint-2.md)**
>
> **[Click here to see the sprint-3 workouts](project/markdowns/sprint/sprint-3.md)**
## 🚀 Installation Steps
You can run the project by following the steps below:
```bash
# 1. Clone repository (optional)
git clone https://github.com/dvaser/Mediary.git
cd Mediary
# 2. Create a virtual environment (.venv)
python -m venv .venv
# 3. Activate the virtual environment (.venv)
# Windows (PowerShell)
.venv\Scripts\Activate.ps1
# If you get a script execution error in PowerShell:
Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
# Windows (CMD)
.venv\Scripts\activate.bat
# Windows (Powershell)
.venv\Scripts\activate
# macOS / Linux
source .venv/bin/activate
# 4. Install the required packages
pip install -r requirements.txt
# 5. Start the application
python main.py
# 6. Log out of the virtual environment (.venv)
deactivate
# (In addition) Transfer libraries used (requirements.txt)
pip freeze > requirements.txt
```
## Pipeline
```
PDFChunker ---> GeminiEmbedder ---> ChromaDBWrapper ---> Query + Gemini Answer
```
## Structure
```
project/
│
├── code/
│ ├── pdf_prep.py # PDFChunker
│ ├── model/
│ │ ├── gemini.py # GeminiEmbedder + GeminiAnswerGenerator
│ │ └── chroma.py # ChromaDBWrapper
│ └── pipeline.py # RAGPipeline
│
├── main.py # Uygulamanın başlangıç noktası
└── chromadb_persist/ # Vektör veritabanı dosyaları (otomatik oluşur)
```
## Product Features
> 🧠 **AI-Powered Diagnosis Prediction:** Predicts possible diseases based on the patient's medical history.
>
> 🔬 **Test Recommendation System:** Lists diagnostic tests relevant to the suspected condition and submits them for physician approval.
>
> 📊 **Test Result Analysis:** Compares results against normal reference ranges and interprets them accordingly.
>
> 💬 **AI-Assisted Interpretation:** Simplifies and summarizes all medical data into clear, understandable reports.
>
> 🌐 **Web-Based Interface:** User-friendly input and output panels designed for both patients and healthcare professionals.
>
> 📁 **Database and Knowledge Mapping:** Includes disease–test associations and reference value tables for clinical accuracy.
## Target Audience
* #### *Medical School Students*
* #### *Family Physicians and Internal Medicine Specialists*
* #### *Medical Secretaries and Allied Health Personnel*
* #### *Healthcare Technology Developers*
* #### *Curious Patients and Health-Conscious Individuals*