This is the R-Shiny prototype codebase which implements the CRISP-DM process to empower healthcare professionals, thus instantiating the concept of Self-Service Data Science. Auto-CRISP was developed in 2018 by Niels de Vries at Utrecht University, as part of his MSC research project: Making Machine Learning accessible to Healthcare Professionals for the purpose of predicting Medical Adverse Events.
The prototype design rationale and evaluations have been summarised in the following research paper:
Spruit,M., & Vries,N. de (2021). Self-Service Data Science for Adverse Event Prediction in Electronic Healthcare Records. In Visvizi,A., Lytras,M., & Aljohani,N. (Eds.), Springer Proceedings in Complexity, Research and Innovation Forum 2020: Disruptive Technologies in Times of Change (pp. 517–535). RII 2020, Athens, Greece: Springer.
A clinical employment of Auto-CRISP is described in a research paper which is currently under review. An online demonstration of Auto-CRISP can be found at: https://spru.shinyapps.io/AutoCrisp/.