R Code Repository

Statistical analyses and model logic were organized in R. The local script includes cohort filtering, recoding, descriptive statistics, and tests for group differences.

Open R Script

# Cohort setup
citrue <- NCDBMeningioma_1[
  NCDBMeningioma_1$PALLIATIVE_CARE == 0, ]

pctrue <- NCDBMeningioma_1[
  NCDBMeningioma_1$PALLIATIVE_CARE == 4, ]

plcrecode <- factor(ifelse(
  ciandpctrue$PALLIATIVE_CARE == 4,
  "1", "0"))

agep <- wilcox.test(
  citrue$AGE, pctrue$AGE,
  exact = FALSE)

Python Project (Data Segmentation)

I also contributed to a Python project structure used for segmentation and inference workflows, with reusable training, evaluation, and inference entry points.

gbm_segmentation_project/
|-- Resources/Toby/
|   |-- main.py
|   |-- train.py
|   |-- inference.py
|   |-- train_unetr.py
|   |-- transformer.py
|   |-- utils.py
|   |-- config.py
|   |-- requirements.txt
|   |-- combine_views.ipynb
|   `-- model_train.sh

mode = train | evaluate | inference

Open Python Entry Point

Key Contributions

• Segmented and cleaned national database records for downstream analysis.
• Built reproducible processing and variable-derivation workflows.
• Performed exploratory analysis to inform downstream modeling.
• Assisted with Kaplan-Meier survival analysis and logistic regression modeling.
• Generated publication-ready tables and figure-ready summaries.

Supporting Materials