Software

TOOLS · TRANSPARENCY · REPRODUCIBILITY

Software

Open tools and computational resources from the Miller Lab for research, evidence synthesis, visualization, and scientific inference.

Research tools

Software is part of the Miller Lab’s broader effort to make research more transparent, reproducible, and useful. We develop tools that help organize evidence, clarify assumptions, support analysis, and communicate uncertainty.

Our software projects span clinical research workflows, evidence synthesis, data visualization, open inference, and practical tools for improving how biomedical evidence is interpreted and shared.

Good software does more than automate tasks. It makes assumptions visible, workflows reproducible, and evidence easier to examine.

Available software

skincancerRx

skincancerRx is an R package designed to visualize FDA approvals for skin cancer.

Dec 5, 2022

David M. Miller, Sophia Z. Shalhout

FDA Approvals in Skin Cancer - A Shiny App

FDA Approvals in Skin Cancer is a Shiny application designed to visualize FDA approvals for skin cancer.

Nov 26, 2022

David M. Miller, Sophia Z. Shalhout

StoryboardR

StoryboardR is an R package and Shiny application designed to visualize Real-World Data from clinical tumor registries.

Feb 26, 2022

David M. Miller, Sophia Z. Shalhout

BodyMapR

BodyMapR is an R package and Shiny application that generates anatomical visualizations of cancer lesions from structured data.

Dec 26, 2021

David M. Miller, Sophia Z. Shalhout

GENETEX

GENETEX is a R package and Shiny application designed to facilitate data abstraction from genomic reports for clinical research.

Sep 26, 2021

David M. Miller, Sophia Z. Shalhout

Generalizable EHR Labs Abstraction (eLAB) Pipeline

eLAB is a clinical informatics pipeline that pulls large-scale data from the EHR, wrangles and remaps for import into REDCap.

Nov 18, 2020

Sophia Z. Shalhout, David M. Miller