We conducted IR to recognize the challenges in implementing eHealth innovations in the context of maternal and newborn healthcare using the implementation research logic model (IRLM). Therefore, this paper aims to describe the practical application of IRLM to design, execute and evaluate eHealth ...
The core of the book consists of four practical examples, covering all the main software functionality and allowing the users to get to know the basics of modeling and simulation with AnyLogic. Manufacturing (job shop model) Healthcare (epidemic model) Marketing research (consumer choice model)...
Examples of use are short-term production scheduling or transportation planning. Model building support We provide unlimited consultative support for hard or even vague modeling issues. A question like “How do I model this object?” is a perfectly valid question. Average response time is less ...
HealthcareApis/workspaces/iotconnectors Microsoft.HealthModel/healthmodels Microsoft.HybridContainerService/provisionedClusters microsoft.hybridnetwork/networkfunctions microsoft.hybridnetwork/virtualnetworkfunctions microsoft.insights/autoscalesettings microsoft.insights/components Microsoft.Insights/datacollectionrule...
I want everyone to have access to modern healthcare, reliable electricity, and modern amenities (assuming they also want that access), but this is something we need to think about as we plan for a sustainable future. Those rapidly growing populations will, hopefully, have access to a high ...
Working from your risk register, you can begin collecting data, scoping risks, and building different scenarios with a model like Open FAIR. We recommend using existing qualitative assessments to prioritize data collection for your first quantitative assessment. Select an event with a high likelihood...
I will give a few examples, but the following specifications do not matter for my results: An object b could be an experience with a given unpleasantness that lasts for one second, and m b-objects could mean m such experiences. In general, I think of m b-objects as m objects of the...
The healthcare dataset of osteoporosis risk prediction has been transformed by a fuzzy logic approach. The considered dataset is transformed (fuzzified) by comparison of three binary variables with each other. Subsequently, to the transformation, the dataset goes through the inference engine where infe...
The two key elements of a digital twin are a dynamic simulation model and data that reflects the current state of a live system. With the model and the data, it is possible to build powerful digital twin software for experimentation, analysis, and communication, so that you can ask what-...
While deep reinforcement learning is a new development in the world of artificial intelligence, and still mainly considered a research topic, simulation modeling has been in daily practical use for decades. It has a very mature community with a vast body of real-world examples. ...