Evaluating biases in the healthcare process which impact results
MIT License
Evaluation of the impact of process biases in healthcare.
GEBI: Global Explanations for Bias Identification. Open source code for discovering bias in data ...
Interactive Streamlit app to make sense of FFT Feedback - for a responsive Primary Care Service
Evaluating the reproducibility of mortality prediction studies in the MIMIC-III database
Evaluation of the Sepsis-3 guidelines in MIMIC-III
Lecture notes for 'Interpretable Machine Learning' at UoW. Summer semester 2020/2021
Interpretability Techniques to Build Robust AI Applications
A template for conducting an analysis in the MIMIC clinical databases
Evaluating methods to improve model transfer for intensive care unit models
just another dangerous situation
Python code parsing data from PhysioNet Challenge 2012
Real time mortality prediction in the MIMIC-III database
Medical data processing and ML workshops
Notebooks to investigate data set bias in audio embeddings
Replication of the arterial line study in MIMIC-IV