An Explainable Bioinformatics Platform for Multi-Cancer Classification using RNA-Seq Gene Expression Data.
- Data preprocessing pipeline
- Automatic feature scaling
- Multi-model benchmarking
- Logistic Regression
- Decision Tree
- Random Forest
- Automatic evaluation reports
- Automatic confusion matrix generation
- Automatic model comparison
- Automatic model saving
- Breast Cancer (BRCA)
- Lung Adenocarcinoma (LUAD)
- Colon Adenocarcinoma (COAD)
- Kidney Renal Clear Cell Carcinoma (KIRC)
- Liver Hepatocellular Carcinoma (LIHC)
- Python
- Pandas
- NumPy
- Scikit-learn
- XGBoost
- SHAP
- Plotly
- Streamlit
- Dataset Preparation
- Exploratory Data Analysis
- Data Preprocessing
- Logistic Regression
- Decision Tree
- Random Forest
- KNN
- SVM
- XGBoost
- Hyperparameter Tuning
- SHAP Explainability
- Streamlit Dashboard