Citation
========

If you use Case-Explainer in your research, please cite:

BibTeX
------

.. code-block:: bibtex

   @software{case_explainer2025,
     author = {Whitten, Paul and Wolff, Francis and Papachristou, Chris},
     title = {Case-Explainer: General-Purpose Case-Based Explainability},
     year = {2025},
     url = {https://github.com/paulwhitten/case-explainer}
   }

Related Publications
--------------------

The case-based explainability approach implemented in this package was validated in:

**Hardware Trojan Detection**

* Whitten, P., Wolff, F., & Papachristou, C. (2024). "Explainable Hardware Trojan Detection 
  Using Case-Based Reasoning." *Journal of Electronic Testing: Theory and Applications (JETTA)*.

This work demonstrated 99.9% correspondence on hardware trojan detection with 56,959 samples,
showing the effectiveness of case-based explanations for security-critical applications.

**Theoretical Foundation**

The general approach is inspired by:

* Caruana, R., Kangarloo, H., Dionisio, J., Sinha, U., & Johnson, D. (1999). 
  "Case-based explanation of non-case-based learning methods." 
  *Proceedings of the AMIA Symposium*, 212-215.

Acknowledgments
---------------

* Built with scikit-learn, NumPy, and matplotlib
* Inspired by interpretable machine learning research
* Validated across medical, financial, and security domains