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R-Compatibility-Sim-Study Public
A simulation study looking at which combinations of missing data handling methods across a prediction model's pipeline are compatible, and which ones lead to bias.
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Two-parameter Bayesian logistic dose-escalation model to find the maximum tolerated dose (MTD) of HTL0039732 agent alone and in combination with a backbone agent in patients with solid tumours.
clinical-trials cancer-research clinical-research adaptive-design dose-escalation bayesian-logistic-regressionR UpdatedMar 14, 2024 -
ML-algorithms-Sim-Study Public
A simulation study completed during a visit at the Microsoft Research, Cambridge (May-Sept, 2022)
python simulation machine-learning-algorithms neural-networks missing-data boosting-algorithms classifiersPython UpdatedMar 5, 2024 -
NCORR-EHR-Study Public
Implications for bias in estimated predictive performance when using different approaches to handle missing data across validation and implementation of a clinical prediction model: examples from c…
R UpdatedMar 5, 2024 -
CPM-Literature-Review Public
A literature review exploring how missing data was handled across the pipeline of commonly used UK clinical prediction models
missing-data real-world-evidence literature-review missing-data-imputation clinical-prediction-modelsR UpdatedAug 10, 2023 -
medspaCy_MedInfo_2023 Public
Forked from medspacy/medspaCy_MedInfo_2023Supplementary information for the medspaCy workshop presentation at MedInfo 2023 in Sydney, Australia
Jupyter Notebook UpdatedJul 7, 2023
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