Abstract
Cancer registries are important tools in the fight against cancer. At the heart of these registries is the data collection and coding process. Ruled by complex international standards and numerous best practices, operators are easily overwhelmed. In this paper, a system is presented to assist operators in the interpretation of best medical coding practices. By leveraging the arguments used by the coding experts to determine the best coding option, the proposed system is designed to answer the coding questions from operators and provide an answer associated with a partial explanation for the proposed solution.
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Notes
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An adenopathy is an enlargement of lymph nodes, likely due to the cancer.
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The morphology describes the type and behavior of the cells that compose the tumor.
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For primary lung adenocarcinoma, TTF1 marker is usually positive.
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Acknowledgments
The authors wish to thank the anonymous reviewers for their remarks which have helped in improving the quality of the paper. The first author would also like to thank the Fondation Cancer for their financial support.
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Schnell, M., Couffignal, S., Lieber, J., Saleh, S., Jay, N. (2017). Case-Based Interpretation of Best Medical Coding Practices—Application to Data Collection for Cancer Registries. In: Aha, D., Lieber, J. (eds) Case-Based Reasoning Research and Development. ICCBR 2017. Lecture Notes in Computer Science(), vol 10339. Springer, Cham. https://doi.org/10.1007/978-3-319-61030-6_24
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