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Improving Medical Coding with Case-Based Reasoning -Evaluation for Cancer Registries

Abstract : Providing a comparable and consistent description of any entity is a difficult task. Vocabulary, semantics and objectives need to be very clearly defined and followed. The same can be said about cancer registries. They are an essential element in the fight against cancer. Among the main tasks of these registries is the data collection and coding process of cancer cases. To ensure comparable and consistent data, complex international standards and numerous best coding practices have been defined. Unfortunately this complexity can easily overwhelm operators, which are the people in charge of data collection and coding. While coding experts can help operators in their job, this represents a great burden on their precious time. To assist operators in their task and reduce the burden on coding experts, a coding assistant relying on arguments was designed and implemented. This system provides answers and a partial explanation, using arguments in favor and against answers. In this paper, a first evaluation of this system is presented, testing the system on real topography questions asked by operators.
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Submitted on : Tuesday, November 19, 2019 - 4:08:52 PM
Last modification on : Tuesday, March 8, 2022 - 4:52:14 PM


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  • HAL Id : hal-02370896, version 1



Michael Schnell, Sophie Couffignal, Jean Lieber, Nicolas Jay. Improving Medical Coding with Case-Based Reasoning -Evaluation for Cancer Registries. Workshop on CBR in the Health Science at ICCBR-2019, Sep 2019, Otzenhausen, Germany. ⟨hal-02370896⟩



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