Abstract: The COVID- 19 epidemic has needed lesser nanosecond- to- nanosecond urgency of patient treatment in ferocious Care Units( ICUs), rendering the use of Randomized Controlled Trials( RCTs) too slow to be effective for treatment discovery. There's a need for dexterity in clinical exploration, and the use of data wisdom to develop prophetic models for patient treatment is a implicit result. We propose the use of an nimble data wisdom frame grounded on the Scrumban frame used in software development. Scrumban is an iterative frame, where in each replication larger problems are broken down into simple do- suitable tasks for data. The two sides unite nearly in formulating clinical questions and developing and planting prophetic models into clinical settings. What's truly demanded are data scientist and croaker
hookups icing close collaboration between the two sides in using these tools to develop clinically useful prophetic models to meet the demands of the COVID- 19 healthcare geography.
Keywords: Agile Scrumban, Minimal Viable Model,Cloud Computing, Predictive model, Amazon Web Services
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DOI:
10.17148/IJARCCE.2023.12656
