ArticleJournal of digital imaging2015
Business Model for the Security of a Large-Scale PACS, Compliance with ISO/27002:2013 Standard.
Article in Journal of digital imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Segmentation and 3D Visualization of Spinal Motion Segments from MSCT Images Using a 3D U‑Net Framework.Journal of imaging informatics in medicine · 2026Article
- Transforming Medical Imaging: The Role of Artificial Intelligence Integration in PACS for Enhanced Diagnostic Accuracy and Workflow EfficiencyCurrent medical imaging · 2025Review
- Cybersecurity in PACS and Medical Imaging: an Overview.Journal of digital imaging · 2020Review
- Limitations in and Solutions for Improving the Functionality of Picture Archiving and Communication System: an Exploratory Study of PACS Professionals' Perspectives.Journal of digital imaging · 2019Observational
- A Dependable Massive Storage Service for Medical Imaging.Journal of digital imaging · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data security is a critical issue in an organization; a proper information security management (ISM) is an ongoing process that seeks to build and maintain programs, policies, and controls for protecting information. A hospital is one of the most complex organizations, where patient information has not only legal and economic implications but, more importantly, an impact on the patient's health. Imaging studies include medical images, patient identification data, and proprietary information of the study; these data are contained in the storage device of a PACS. This system must preserve the confidentiality, integrity, and availability of patient information. There are techniques such as firewalls, encryption, and data encapsulation that contribute to the protection of information. In addition, the Digital Imaging and Communications in Medicine (DICOM) standard and the requirements of the Health Insurance Portability and Accountability Act (HIPAA) regulations are also used to protect the patient clinical data. However, these techniques are not systematically applied to the picture and archiving and communication system (PACS) in most cases and are not sufficient to ensure the integrity of the images and associated data during transmission. The ISO/IEC 27001:2013 standard has been developed to improve the ISM. Currently, health institutions lack effective ISM processes that enable reliable interorganizational activities. In this paper, we present a business model that accomplishes the controls of ISO/IEC 27002:2013 standard and criteria of security and privacy from DICOM and HIPAA to improve the ISM of a large-scale PACS. The methodology associated with the model can monitor the flow of data in a PACS, facilitating the detection of unauthorized access to images and other abnormal activities.
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What OpenQuestion holds
Registered trials
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.