Quantified Sleep: Machine learning techniques for observational n-of-1 studies.
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Updated
May 28, 2021 - Jupyter Notebook
Quantified Sleep: Machine learning techniques for observational n-of-1 studies.
Taking causal inference to the extreme!
Web application to run meta-analyses
Implementation for the paper "Detecting critical treatment effect bias in small subgroups"
Course materials for "Biostatistics: Case Studies"
Simulation for "Method-of-Moments Inference for GLMs and Doubly Robust Functionals under Proportional Asymptotics"
Anonymously aggregated analyses on the relationships between thousands of symptoms and potential factors.
Accounting for hidden confounders in estimates of dose-response curves from observational data.
Reports intended to help you and your physician to gain insight into the root causes and effective solutions to help you minimize your symptoms.
A Critical Appraisal Plot Visualiser for Risk of Bias Assessments in Systematic Reviews and Meta-Analyses
A Traffic light Plot Visualiser for Newcastle–Ottawa Scale (NOS) risk-of-bias assessments for Meta-analysis.
Obspy code that generates continuous spectrograms from FDSN listed seismic stations.
Open Source Tool for Human Affect Recording inspired by Human Affect Recording Tool - Implemented with Django for most compatibility
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