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Semantically Describing Predictive Models for Interpretable Insights into Lung Cancer Relapse [Draft]

SemDesLC predicts lung cancer relapse likelihood, providing oncologists with patient-centric and population-centric analysis. Our approach bridge the gap and fulfill the needs of three different type of users: KG builders, analysts and consumers. This repository contains all the necessary scripts and instructions to reproduce the experiments.

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Cite this as

Yashrajsinh Chudasama, Disha Purohit, Philipp D. Rohde, Enrique Iglesias, Maria Torrente, Maria-Esther Vidal (2024). Dataset: Semantically Describing Predictive Models for Interpretable Insights into Lung Cancer Relapse. https://doi.org/10.57702/z26cs7i9

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Additional Info

Field	Value
Created	September 16, 2024
Last update	September 16, 2024
License	cc-by: Creative Commons Attribution
Source	https://github.com/SDM-TIB/SemDesLC
Defined In	https://doi.org/10.3233/SSW240012
Author	Yashrajsinh Chudasama
More Authors	Disha Purohit Philipp D. Rohde Enrique Iglesias Maria Torrente Maria-Esther Vidal
Author Email	Yashrajsinh Chudasama
Maintainer	Yashrajsinh Chudasama
Maintainer Email	Yashrajsinh Chudasama
Language	English
Access Rights	Public