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04/26/2023
Towards clinical AI fairness: A translational perspective
Artificial intelligence (AI) has demonstrated the ability to extract ins...
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04/14/2023
Federated and distributed learning applications for electronic health records and structured medical data: A scoping review
Federated learning (FL) has gained popularity in clinical research in re...
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04/07/2023
A roadmap to fair and trustworthy prediction model validation in healthcare
A prediction model is most useful if it generalizes beyond the developme...
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03/01/2023
FedScore: A privacy-preserving framework for federated scoring system development
We propose FedScore, a privacy-preserving federated learning framework f...
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10/15/2022
Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques
Objective: The proper handling of missing values is critical to deliveri...
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06/08/2022
Balanced background and explanation data are needed in explaining deep learning models with SHAP: An empirical study on clinical decision making
Objective: Shapley additive explanations (SHAP) is a popular post-hoc te...
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02/17/2022
AutoScore-Ordinal: An interpretable machine learning framework for generating scoring models for ordinal outcomes
Background: Risk prediction models are useful tools in clinical decision...
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01/10/2022
A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort
Risk scores are widely used for clinical decision making and commonly ge...
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11/22/2021
Benchmarking Predictive Risk Models for Emergency Departments with Large Public Electronic Health Records
There is a continuously growing demand for emergency department (ED) ser...
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11/18/2021
HRnV-Calc: A software package for heart rate n-variability and heart rate variability analysis
Objective: Heart rate variability (HRV) has been proven to be an importa...
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10/06/2021
Shapley variable importance clouds for interpretable machine learning
Interpretable machine learning has been focusing on explaining final mod...
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07/21/2021
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies
Objective: Temporal electronic health records (EHRs) can be a wealth of ...
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07/13/2021
AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data
Background: Medical decision-making impacts both individual and public h...
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06/13/2021
