UPDATE:
current version of the repository at: https://github.com/digital-ECMT/CORONET_tool
CORONET is an online tool to support decisions regarding hospital admissions or discharge in cancer patients presenting with symptoms of COVID-19 and the likely severity of illness. It is based on real world patient data.
The tool is available at: https://coronet.manchester.ac.uk/
This repository contains code to develop a CORONET model version 1 used in the tool to generate recommendation.
Detailed description of the process of developing CORONET can be found in our publication:
Establishment of CORONET; COVID-19 Risk in Oncology Evaluation Tool to identify cancer patients at low versus high risk of severe complications of COVID-19 infection upon presentation to hospital
https://www.medrxiv.org/content/10.1101/2020.11.30.20239095v1
To learn more about how the score was calculated and to see a global explanation for the model and local explanations for individual patients in the training cohort, visit: CORONET_explain.ipynb
The code used for the model development can be found here: CORONET_model_dev.ipynb
The code on which the tool is based on, is available here: CORONET_code_for_tool.py
Detailed description of the process of developing CORONET can be found in our publication:
Establishment of CORONET; COVID-19 Risk in Oncology Evaluation Tool to identify cancer patients at low versus high risk of severe complications of COVID-19 infection upon presentation to hospital
- version 1 available at medRxiv. https://www.medrxiv.org/content/10.1101/2020.11.30.20239095v1
- version 2 published in JCO Clinical Cancer Informatics