Update README.md

README.md

@@ -4,43 +4,53 @@ emoji: 🏥
 colorFrom: indigo
 colorTo: blue
 sdk: streamlit
-sdk_version: "1.18.1"
+sdk_version: "1.24.1"
 app_file: app.py
 pinned: false
 ---
-🏥 AI Clinical Intelligence Hub
-Welcome to the AI Clinical Intelligence Hub, an advanced, AI-powered platform designed to revolutionize clinical data analysis and decision-making. Leveraging OpenAI's GPT-4, this hub provides comprehensive tools for data ingestion, exploratory data analysis, statistical testing, machine learning model training, clinical rules execution, KPI monitoring, diagnosis support, treatment recommendations, and access to a robust Medical Knowledge Base.
+# 🏥 AI Clinical Intelligence Hub
 
+Welcome to the **AI Clinical Intelligence Hub**, an advanced, AI-powered platform designed to revolutionize clinical data analysis and decision-making. Leveraging **OpenAI's GPT-4**, this hub provides comprehensive tools for data ingestion, exploratory data analysis, statistical testing, machine learning model training, clinical rules execution, KPI monitoring, diagnosis support, treatment recommendations, and access to a robust Medical Knowledge Base.
 
-🚀 Features
-Data Ingestion: Seamlessly upload and connect to CSV files or SQL databases.
-Exploratory Data Analysis (EDA): Gain insights into your datasets with comprehensive EDA reports.
-Temporal Pattern Analysis: Analyze time-series data to identify trends and seasonality.
-Comparative Statistics: Perform hypothesis testing and comparative statistical analyses.
-Distribution Analysis: Visualize data distributions using customizable plots.
-Machine Learning: Train and evaluate Logistic Regression models on your data.
-Clinical Rules Engine: Define and execute clinical rules to automate decision-making.
-KPI Monitoring: Define, calculate, and monitor Key Performance Indicators (KPIs).
-Diagnosis Support: Utilize machine learning models to assist in clinical diagnoses.
-Treatment Recommendations: Generate treatment suggestions based on patient data.
-Medical Knowledge Base: Access comprehensive medical information powered by OpenAI's GPT-4 and retrieve relevant PubMed abstracts.
-📸 Screenshots
-Dashboard Overview
+![AI Clinical Intelligence Hub Banner](banner.png)
+
+## 🚀 Features
+
+- **Data Ingestion**: Seamlessly upload and connect to CSV files or SQL databases.
+- **Exploratory Data Analysis (EDA)**: Gain insights into your datasets with comprehensive EDA reports.
+- **Temporal Pattern Analysis**: Analyze time-series data to identify trends and seasonality.
+- **Comparative Statistics**: Perform hypothesis testing and comparative statistical analyses.
+- **Distribution Analysis**: Visualize data distributions using customizable plots.
+- **Machine Learning**: Train and evaluate Logistic Regression models on your data.
+- **Clinical Rules Engine**: Define and execute clinical rules to automate decision-making.
+- **KPI Monitoring**: Define, calculate, and monitor Key Performance Indicators (KPIs).
+- **Diagnosis Support**: Utilize machine learning models to assist in clinical diagnoses.
+- **Treatment Recommendations**: Generate treatment suggestions based on patient data.
+- **Medical Knowledge Base**: Access comprehensive medical information powered by OpenAI's GPT-4 and retrieve relevant PubMed abstracts.
+
+## 📸 Screenshots
+
+![Dashboard Overview](screenshots/dashboard_overview.png)
+*Dashboard Overview*
+
+![Medical Knowledge Search](screenshots/medical_knowledge_search.png)
+*Medical Knowledge Search Interface*
 
-Medical Knowledge Search Interface
+## 🛠️ Installation & Setup
 
-🛠️ Installation & Setup
-Deploying the AI Clinical Intelligence Hub on Hugging Face Spaces is straightforward. Follow the steps below to get your application up and running.
+Deploying the **AI Clinical Intelligence Hub** on **Hugging Face Spaces** is straightforward. Follow the steps below to get your application up and running.
+
+### 1. **Prerequisites**
+
+- **Hugging Face Account**: Ensure you have an account on [Hugging Face](https://huggingface.co/).
+- **OpenAI API Key**: Obtain your API key from [OpenAI](https://platform.openai.com/account/api-keys).
+- **PubMed Email**: A valid email address for accessing PubMed abstracts via Biopython.
+
+### 2. **Clone the Repository**
 
-1. Prerequisites
-Hugging Face Account: Ensure you have an account on Hugging Face.
-OpenAI API Key: Obtain your API key from OpenAI.
-PubMed Email: A valid email address for accessing PubMed abstracts via Biopython.
-2. Clone the Repository
 If you haven't already, clone the repository to your local machine:
 
-bash
-Copy
+```bash
 git clone https://github.com/your-username/ai-clinical-intelligence-hub.git
 cd ai-clinical-intelligence-hub
 3. Configure Environment Variables
@@ -72,7 +82,7 @@ Commit and push your code to your GitHub repository linked to your Hugging Face
 bash
 Copy
 git add .
-git commit -m "Initial commit with OpenAI GPT-4 integration"
+git commit -m "Fix Altair import and update OpenAI SDK"
 git push origin main
 Automatic Deployment:
 
@@ -147,19 +157,20 @@ Returns: A DataFrame with treatment recommendations.
 📦 Dependencies
 The application relies on the following Python packages:
 
-streamlit
-pandas
-numpy
-matplotlib
-seaborn
-scikit-learn
-statsmodels
-pydantic
-biopython
-python-dotenv
-requests
-spacy
-openai
+streamlit>=1.24.1
+pandas>=1.5.3
+numpy>=1.25.2
+matplotlib>=3.7.2
+seaborn>=0.12.2
+scikit-learn>=1.2.2
+statsmodels>=0.14.0
+pydantic>=2.5.3
+biopython>=1.79
+python-dotenv>=1.0.0
+requests>=2.31.0
+spacy>=3.5.3
+openai>=1.8.0
+altair>=5.1.0
 Ensure all dependencies are installed using:
 
 bash
@@ -177,38 +188,6 @@ Hugging Face for hosting and deploying the application.
 📬 Contact
 For questions, feedback, or support, please reach out to [email protected].
 
-📚 Getting Started
-Clone the Repository:
-
-bash
-Copy
-git clone https://github.com/your-username/ai-clinical-intelligence-hub.git
-cd ai-clinical-intelligence-hub
-Set Up Environment Variables:
-
-Hugging Face Spaces: Add OPENAI_API_KEY and PUB_EMAIL in the Secrets section.
-Local Development: Create a .env file with the following content:
-env
-Copy
-OPENAI_API_KEY=your_openai_api_key_here
-[email protected]
-Install Dependencies:
-
-bash
-Copy
-pip install -r requirements.txt
-python -m spacy download en_core_web_sm
-Run the Application Locally (Optional):
-
-bash
-Copy
-streamlit run app.py
-Deploy to Hugging Face Spaces:
-
-Push your code to GitHub.
-Link your GitHub repository to a new Hugging Face Space.
-Ensure Secrets are configured as described above.
-The application will automatically deploy and be accessible via your Space URL.
 🛡️ Security Considerations
 API Keys: Ensure that your OPENAI_API_KEY and PUB_EMAIL are stored securely and never exposed in the codebase.
 Data Privacy: Comply with relevant data protection regulations (e.g., HIPAA, GDPR) when handling sensitive medical data.
@@ -239,43 +218,4 @@ User Authentication: Implement robust user authentication and authorization mech
 Advanced Machine Learning Models: Integrate more sophisticated models for diagnosis and prediction.
 Real-Time Data Streaming: Support real-time data ingestion and analysis for dynamic clinical environments.
 Enhanced Reporting: Develop customizable and exportable report formats (e.g., PDF, DOCX).
-Natural Language Processing (NLP): Enhance the Medical Knowledge Base with advanced NLP capabilities for better query understanding.
-Feel free to customize this template further to better fit your project's specific needs and branding. Including images (like screenshots or banners) can greatly enhance the README's visual appeal and user comprehension.
-
-📄 Example of Filled YAML Front Matter
-Here's how the YAML front matter at the top of your README.md should look with actual values:
-
-yaml
-Copy
----
-title: AI Clinical Intelligence Hub
-emoji: 🏥
-colorFrom: indigo
-colorTo: blue
-sdk: streamlit
-sdk_version: "1.18.1"
-app_file: app.py
-pinned: false
----
-Explanation of Fields:
-
-title: The name of your Space.
-emoji: An emoji representing your Space.
-colorFrom & colorTo: Colors for the gradient theme of your Space's card.
-sdk: The framework you're using (e.g., streamlit).
-sdk_version: The version of the SDK/framework.
-app_file: The main application file (e.g., app.py).
-pinned: Whether to pin this Space on your Hugging Face profile (true or false).
-📊 Customizing Your Hugging Face Space
-To further customize your Space's appearance and functionality, consider the following:
-
-Banner Image: Place a banner.png image in the root of your repository to display a banner at the top of your Space.
-Screenshots: Store screenshots in a screenshots/ directory and reference them in your README.md to showcase features.
-Pinned State: Set pinned: true in the YAML front matter if you want this Space to appear prominently on your profile.
-📚 Additional Resources
-Hugging Face Spaces Documentation
-Streamlit Documentation
-OpenAI GPT-4 API Documentation
-Biopython Entrez Module
-📞 Support
-If you encounter any issues or have questions about deploying or using the AI Clinical Intelligence Hub, please contact [email protected].
+Natural Language Processing (NLP): Enhance the Medical Knowledge Base with advanced NLP capabilities for better query understanding.