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Semantically Describing Predictive Models for Interpretable Insights into Lung Cancer Relapse

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.

Data and Resources

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

DOI retrieved: September 16, 2024

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