Add scripts for patient classification and visualization

- Created `classification.py` for comparing image-level and patient-level classification results using various CNN models.
- Implemented `create_patient_groups.py` to extract features, generate PCA/t-SNE plots, and identify patient groups via K-means clustering.
- Added `figure6.py` to generate boxplots for test accuracy across multiple seeds.
- Developed `simple_patient_tsne.py` to perform t-SNE visualization of patient groups and save results in a manifest file.
- Introduced `simple_patient_manifest.csv` to store patient IDs, classes, image counts, and associated images.

.gitignore

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+# Archive
+.archive/
+
+# Python
+__pycache__/
+*.py[cod]
+*.egg-info/
+dist/
+build/
+
+# Environments
+.env
+.venv
+env/
+venv/
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Sensitive
+*.pem
+*.key
+*.p12
+*.pfx
+credentials*
+secrets*
+*.env.*
+
+# Data (large feature files — regenerate via scripts)
+features/*.npz
+features/*.npy
+
+# Outputs
+plots/*.png
+
+# Jupyter
+.ipynb_checkpoints/
+
+# Conda
+.python-version