Merge pull request #9 from ssciwr/fix_5_link_to_models_paper

Add link to paper, add sentences describing the project, resolves #5

.github/workflows/ci.yml

@@ -33,7 +33,7 @@ jobs:
         run: |
           git clone https://github.com/ZhaoWenzhao/QHCC.git
           cd QHCC
-          python demo_QHCC_XGBoost.py
+          python demo_QHCC_XGBoost_comb.py
   conda-forge:
     strategy:
       fail-fast: false
@@ -61,4 +61,4 @@ jobs:
         run: |
           git clone https://github.com/ZhaoWenzhao/QHCC.git
           cd QHCC
-          python demo_QHCC_XGBoost.py
+          python demo_QHCC_XGBoost_comb.py

README.md

@@ -5,3 +5,12 @@
 [![ci](https://github.com/ssciwr/QHCC/actions/workflows/ci.yml/badge.svg)](https://github.com/ssciwr/QHCC/actions/workflows/ci.yml)
 
 Source code and example notebooks for the [Q-HCC website](https://ssciwr.github.io/QHCC).
+
+## To build the website locally
+
+```bash
+pip install mkdocs-material
+mkdocs serve
+```
+
+The website will then be served locally at http://127.0.0.1:8000/QHCC, and will be updated if any of the markdown files are edited.

docs/data.md

@@ -1,6 +1,6 @@
 # Data
 
-Introduction to the provided datasets.
+Q-HCC - Quality-assured data set for hepatocellular carcinoma.
 
 ## heiData
 

docs/index.md

@@ -1,6 +1,10 @@
 # Welcome to Q-HCC
 
-Some text about what this is...
+The objective of this project is to provide a baseline for performing multi-modal data classification on a novel open multimodal dataset of hepatocellular carcinoma (HCC).
+
+To learn more about the models and how to run them yourself, see the [models](models.md) page.
+
+To learn more about the data and how to download it, see the [data](data.md) page.
 
 ## Quickstart
 

docs/models.md

@@ -1,6 +1,8 @@
 # Models
 
-Example models and data are provided at [github.com/ZhaoWenzhao/QHCC](https://github.com/ZhaoWenzhao/QHCC).
+A paper draft is available at [arXiv:2501.11535](https://arxiv.org/abs/2501.11535). The objective of this paper is to provide a baseline for performing multi-modal data classification on a novel open multimodal dataset of hepatocellular carcinoma (HCC), which includes both image data (contrast-enhanced CT and MRI images) and tabular data (the clinical laboratory test data as well as case report forms).
+
+Example models and pre-processed data are provided at [github.com/ZhaoWenzhao/QHCC](https://github.com/ZhaoWenzhao/QHCC).
 
 In order to run the provided example scripts, you will need to use Python 3.8 or 3.9, and install the required Python libraries.
 
@@ -34,17 +36,17 @@ Alternatively you can install the required Python libraries directly:
 
 === "pip"
     ```bash
-    pip install jupyter numpy pandas pooch pyradiomics simpleitk scikit-learn xgboost
+    pip install jupyter numpy pandas pooch pyradiomics simpleitk "scikit-learn<1.6" xgboost
     ```
 
 === "conda"
     ```bash
-    conda env create -n QHCC jupyter numpy pandas pooch python radiomics::pyradiomics simpleitk scikit-learn xgboost -c conda-forge -c radiomics
+    conda env create -n QHCC jupyter numpy pandas pooch python radiomics::pyradiomics simpleitk "scikit-learn<1.6" xgboost -c conda-forge -c radiomics
     conda activate QHCC
     ```
 
 === "micromamba"
     ```bash
-    micromamba env create -n QHCC jupyter numpy pandas pooch python radiomics::pyradiomics simpleitk scikit-learn xgboost -c conda-forge -c radiomics
+    micromamba env create -n QHCC jupyter numpy pandas pooch python radiomics::pyradiomics simpleitk "scikit-learn<1.6" xgboost -c conda-forge -c radiomics
     micromamba activate QHCC
     ```

environment.yml

@@ -10,5 +10,5 @@ dependencies:
   - python
   - radiomics::pyradiomics
   - simpleitk
-  - scikit-learn
+  - scikit-learn<1.6
   - xgboost

requirements.txt

@@ -4,5 +4,5 @@ pandas
 pooch
 pyradiomics
 simpleitk
-scikit-learn
+scikit-learn<1.6
 xgboost