A hands-on tutorial for analyzing clinical notes, extracting structured information from medical images, and building LLM-powered healthcare applications.
The tutorial consists of two main sessions:
Description: Leveraging OpenAI models to extract clinically relevant insights from free-text medical notes.
Contact: Soungmun Kim (email)
Description: Using OpenAI vision models to extract body composition measurements from InBody report images and convert them into structured Excel data.
Contact: Soungmun Kim (email)
Description: Leveraging OpenAI to learn low-dimensional gene representations from biomedical context. Contact: Sungmin Kwon (email)
To run the tutorial notebooks, follow these steps:
- Click the green Code button (top right) and select Download ZIP.
- Unzip the downloaded file on your local computer.
- Go to Google Colab
- Click Open Colab button (top right)
- Select the Upload tab and upload the tutorial notebooks (.ipynb) from the extracted folder:
- Session1/Tutorial1_OpenRouter.ipynb
- Session2/Tutorial2ipynb
- Session3/Tutorial3.ipynb
- After the upload is complete, each notebook will open in Google Colab and is ready to run.
The API Key required for the practice can be found at the link below.
Note: This API Key is strictly for use during the KOGO workshop sessions only.
The API Key required for the practice can be found at the link below.
Note: This API Key is strictly for use during the KOGO workshop sessions only.
After opening the notebook, find the API key field:
API_KEY = ""Copy the provided API key and paste it between the quotation marks (" "), as shown below:
API_KEY = "YOUR_API_KEY_HERE"Important:
YOUR_API_KEY_HEREis only an example. Replace it with the API key provided for the workshop.
Do not remove the quotation marks (" ").