des-ist: A Simulation Framework to Streamline Event-Based In Silico Trials

Kolk, Max van der; Miller, Claire; Padmos, Raymond M.; Azizi, Victor; Hoekstra, Alfons G.

doi:10.1007/978-3-030-77967-2_53

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…The surrogate thrombectomy model was integrated into our IST framework, 'des-ist' [18,26] . The des-ist framework provides easy integration of multiple data-driven and mechanistic models for running (event-based) ISTs.…”

Section: Integration Into the In Silico Trial Frameworkmentioning

confidence: 99%

“…The des-ist framework provides easy integration of multiple data-driven and mechanistic models for running (event-based) ISTs. Models are included into the framework in independent Docker [27] or Singularity [28] containers, and inputs and outputs are linked using a common API [26] . For the ISTs used in this paper, the simulation steps were:…”

Section: Integration Into the In Silico Trial Frameworkmentioning

confidence: 99%

See 1 more Smart Citation

In silico thrombectomy trials for acute ischemic stroke

Miller

Konduri

Bridio

et al. 2023

Computer Methods and Programs in Biomedicine

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Section: Integration Into the In Silico Trial Frameworkmentioning

confidence: 99%

Section: Integration Into the In Silico Trial Frameworkmentioning

confidence: 99%

In silico thrombectomy trials for acute ischemic stroke

Miller

Konduri

Bridio

et al. 2023

Computer Methods and Programs in Biomedicine

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“…Both resourcing and productivity measures are inputs into the model. Reducing elective lengths-of-stay and delayed discharges are national priorities (Wall et al 2022). This means that healthcare planners, managers, and clinicians are required to work together to determine the most likely combinations of parameters, accounting for other system components such as workforce.…”

Section: Overview Of the Des Modelmentioning

confidence: 99%

Deploying Healthcare Simulation Models Using Containerization and Continuous Integration

Harper,

Monks,

Manzi

2023

Preprint

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Methods or approaches from disciplines outside of OR Modeling and Simulation (M&S) can potentially increase the functionality of simulation models. In healthcare research, where simulation models are commonly used, we see few applications of models that can easily be deployed by other researchers or by healthcare stakeholders. Models are treated as disposable artifacts, developed to deliver a set of results for stakeholders or for publication. By utilising approaches from software engineering, M&S researchers can develop models that are intended to be deployed for re-use. We propose one potential solution to deploying free and open source simulations using containerisation with continuous integration. A container provides a self-contained environment that encapsulates the model and all its required dependencies including the operating system, software, and packages. This overcomes a significant barrier to sharing models developed in open source software, which is dependency management. Isolating the environment in a container ensures that the simulation model behaves the same way across different computing environments. It also means that other users can interact with the model without installing software and packages, supporting both use and re-use, and reproducibility of results. We illustrate the approach using a model developed for orthopaedic elective recovery planning, developed with a user-friendly interface in Python, including a clear set of steps to support M&S researchers to deploy their own models using our hybrid framework.

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