The Ensemble Tree-based Machine Learning Algorithm to Predict
Acute Kidney Replacement Therapy in Critically-ill Patient (eT-AKRT)
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Notice: This is the previous version. We suggest using the pML-AKRT application. The eT-AKRT application is deprecated.
eT-AKRT application (deprecated)
eT-AKRT application (deprecated)
go to pML-AKRT
Predicted Acute Kidney Replacement Therapy within 7 days of the Critically ill patient.
This is a beta-version (version 0.9). The models were trained and tested on data from SEA-AKI study. This data was provided by Dr. Nattachai Srisawat. The complete experiment method and results have been prepared and will be published soon. However, The performance of models is partially reported below. The model construction, experiment, and web development have been done by Dr. Wanjak Pongsittisak. For more information or any suggestion, don't hesitate to get in touch with me.
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