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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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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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10/28/2022
SMART-EXAM: Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials
Dynamic treatment regimes (DTRs) are sequences of decision rules that re...
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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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03/24/2022
Making SMART decisions in prophylaxis and treatment studies
The optimal prophylaxis, and treatment if the prophylaxis fails, for a d...
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03/17/2022
Micro-Randomized Trial with Flexible Design and Sample Size Considerations
Technological advancements have made it possible to deliver mobile healt...
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03/04/2022
Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions
Reinforcement learning (RL) is acquiring a key role in the space of adap...
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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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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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07/13/2021
A Penalized Shared-parameter Algorithm for Estimating Optimal Dynamic Treatment Regimens
A dynamic treatment regimen (DTR) is a set of decision rules to personal...
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06/13/2021
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data
Scoring systems are highly interpretable and widely used to evaluate tim...
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03/31/2021
Planning SMARTs: Sample size estimation for comparing dynamic treatment regimens using longitudinal count outcomes with excess zeros
In many health domains such as substance-use, outcomes are often counts ...
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07/27/2020
Multi-Level Micro-Randomized Trial: Detecting the Proximal Effect of Messages on Physical Activity
Technological advancements in mobile devices have made it possible to de...
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09/07/2019
Estimating the Optimal Linear Combination of Biomarkers using Spherically Constrained Optimization
In the context of a binary classification problem, the optimal linear co...
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04/22/2019
A distribution-free smoothed combination method of biomarkers to improve diagnostic accuracy in multi-category classification
Results from multiple diagnostic tests are usually combined to improve t...
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01/25/2019
A Sequential Significance Test for Treatment by Covariate Interactions
Due to patient heterogeneity in response to various aspects of any treat...
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08/22/2018