Evidence map›Paper›PMID 24967283›Full record

ReviewISRN radiology2013

The application of use case modeling in designing medical imaging information systems.

Reza Safdari, Jebraeil Farzi, Marjan Ghazisaeidi, Mahboobeh Mirzaee, Azadeh Goodini

Abstract readReview
In one paragraph

Review in ISRN radiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Reza SafdariDepartment of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran 09821-141556183, Iran.
Jebraeil FarziDepartment of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran 09821-141556183, Iran.
Marjan GhazisaeidiDepartment of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran 09821-141556183, Iran.
Mahboobeh MirzaeeDepartment of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran 09821-141556183, Iran.
Azadeh GoodiniDepartment of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran 09821-141556183, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction. The essay at hand is aimed at examining the application of use case modeling in analyzing and designing information systems to support Medical Imaging services. Methods. The application of use case modeling in analyzing and designing health information systems was examined using electronic databases (Pubmed, Google scholar) resources and the characteristics of the modeling system and its effect on the development and design of the health information systems were analyzed. Results. Analyzing the subject indicated that Provident modeling of health information systems should provide for quick access to many health data resources in a way that patients' data can be used in order to expand distant services and comprehensive Medical Imaging advices. Also these experiences show that progress in the infrastructure development stages through gradual and repeated evolution process of user requirements is stronger and this can lead to a decline in the cycle of requirements engineering process in the design of Medical Imaging information systems. Conclusion. Use case modeling approach can be effective in directing the problems of health and Medical Imaging information systems towards understanding, focusing on the start and analysis, better planning, repetition, and control.

Identifiers

PMID24967283
PMCPMC4045551

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.