vamsireddy235/Endometrial-Receptivity-Analysis-ML — reverse-engineered prompt

Build me a simple Streamlit web app for an AI based Endometrial Receptivity Analysis project. I want clinicians or researchers to be able to load the gene expression dataset, see clean charts of the endometrial gene expression patterns, train and compare machine learning models, and get a prediction for the best embryo transfer window.

The app should feel polished and easy to use, not like a raw notebook. Include sections for dataset overview, visualizations, model training, model comparison, and a prediction page where a user can enter or upload patient gene expression values and see the receptivity result. Compare models like XGBoost, Random Forest, and Logistic Regression using accuracy, precision, recall, and F1 score.

Please use the existing CSV data in the project if possible, keep the code organized, and make sure it runs locally with the requirements file. Add clear labels and short explanations so a medical or research user can understand the results. Also include a small note that this is for research support and not a final medical diagnosis.