This a repository collecting shiny apps I have been generating
b) VCExplorer_CT is an advanced version of IME_Score2. The idea is to display some parameters from a virtual observational cohort especially tailored towards fitness and prevention. VCExplorer_CT App
c) IME_Score2 is very similar to VCExplorer_CT. There are no wearables data involved. IME_Score2 App
e) HRV_V2 is different. It tries to displays RR_intervals and BPM from cardio measurements coming from wearables (usually 24hrs). From these measurements a lot of derived parameters are produced. See here for details. A PCA for the cohort is provided and finally a set of gauge indicators will try to summarize the stress level of probands. HRV_V2
f) This Shiny Hospitalization app has to do with the choice of best parameter to obtain the more realistic hospitalization time for a cohort in order to obtain a target Kaplan-Meier plot.
g) Public COVID-19 reference data have been used for the following Shiny for COVID-19 Hospitalization. Here a comparison through the Kaplan-Meier plots is provided so that the parameters chosen for the virtual cohort can be checked against the real-world data.
h) Starting from data reported in a glioblastoma trial, Takoua Korchani and me developed a Virtual Cohort which generates n patients with either Grad_I or Grad_IV glioblastoma and which can be visualized here
If you decide for direct run clicking links under mybinder, it might take few minutes to build the underlining virtual machine, so be patient and let it run.
To build locally:
- Install Docker if required
- Create a virtual environment and install repo2docker from PyPI.
- Clone this repository
- Depending on the permissions, you might have to run the command as an admin and give --user-id xxxx and --user-name name
pip install jupyter-repo2docker git clone https://github.com/agiani99/R_shinyapps.git cd R_shinyapps repo2docker .