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Record W4233834300 · doi:10.32920/ryerson.14653233.v1

A methodology using UML & SADT to develop an effective business model in healthcare

2021· preprint· en· W4233834300 on OpenAlexaboutno aff
Akram Kamal El-Ashy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsUnified Modeling LanguageBusiness process modelingBusiness Process Model and NotationProcess managementComputer scienceFunction (biology)Process modelingBusiness modelModeling languageBusiness processArtifact-centric business process modelBusiness ruleKnowledge managementBusinessOperations managementEngineeringWork in processProgramming languageMarketing

Abstract

fetched live from OpenAlex

A business process model is an abstraction of business funcionality in terms of modeling the goals, processes, objects and any other associated events of an enterprise. An effective business model can show how an enterprise and its subsets function today, and how one may plan for it to function in the future. Effective business modeling to gain insights towards improvements in hospital areas has been used infrequently by industrial engineers. This thesis presents a methodology using UML (Unified Modeling language) and SADT (Structured Analysis & Design Technique) that may be utilized to develop an effective business process model in the medical imaging area of a major Canadian hospital (St. Michael's Hospital). The effectiveness of this business model may clear the way towards a comprehensive analysis for improvements.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.368
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.197
GPT teacher head0.378
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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