EMPAIA App Interface: An open and vendor-neutral interface for AI applications in pathology

Abstract

Background and objective: Artificial intelligence (AI) apps hold great potential to make pathological diagnoses more accurate and time efficient. Widespread use of AI in pathology is hampered by interface incompatibilities between pathology software. We studied the existing interfaces in order to develop the EMPAIA App Interface, an open standard for the integration of pathology AI apps. Methods: The EMPAIA App Interface relies on widely-used web communication protocols and containerization. It consists of three parts: A standardized format to describe the semantics of an app, a mechanism to deploy and execute apps in computing environments, and a web API through which apps can exchange data with a host application. Results: Five commercial AI app manufacturers successfully adapted their products to the EMPAIA App Interface and helped improve it with their feedback. Open source tools facilitate the adoption of the interface by providing reusable data access and scheduling functionality and enabling automatic validation of app compliance. Conclusions: Existing AI apps and pathology software can be adapted to the EMPAIA App Interface with little effort. It is a viable alternative to the proprietary interfaces of current software. If enough vendors join in, the EMPAIA App Interface can help to advance the use of AI in pathology.

@Article{romberg2022api,
  author   = {Daniel Romberg and Klaus Strohmenger and Christoph Jansen and Tobias Küster and Nick Weiss and Christian Geißler and Tomasz Sołtysiński and Michael Takla and Peter Hufnagl and Norman Zerbe and André Homeyer},
  title    = {{EMPAIA} App interface: An open and vendor-neutral interface for {AI} applications in pathology},
  journal  = {Computer Methods and Programs in Biomedicine},
  year     = {2022},
  volume   = {215},
  pages    = {106596},
  issn     = {0169-2607},
  doi      = {https://doi.org/10.1016/j.cmpb.2021.106596},
  keywords = {Artificial intelligence, Interface, Pathology, Whole-slide image, Web service, Containerization},
  url      = {https://www.sciencedirect.com/science/article/pii/S0169260721006702},
}
Autoren:
Daniel Romberg, Klaus Strohmenger, Christoph Jansen, Tobias Küster, Nick Weiss, Christian Geißler, Tomasz Soltysinski, Michael Takla, Peter Hufnagl, Norman Zerbe, Andre Homeyer
Kategorie:
Journal
Jahr:
2022
Ort:
Computer Methods and Programs in Biomedicine
Link: