ReviewJournal of digital imaging2018
Transforming Dermatologic Imaging for the Digital Era: Metadata and Standards.
Review in Journal of digital imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed, 42 citations in OpenAlex.
- DermIDS: Dermatology imaging data structure for scalable and interoperable AI systems.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- Breaking data silos: incorporating the DICOM imaging standard into the OMOP CDM to enable multimodal research.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- MST-AI: Skin Color Estimation in Skin Cancer Datasets.Journal of imaging · 2025Article
- Unlocking the Potentials of Large Language Models in Orthodontics: A Scoping Review.Bioengineering (Basel, Switzerland) · 2024Article
- Potential Benefits of Non-Fungible Tokens (NFTs) and Blockchain Technology in Dermatology.Dermatology practical & conceptual · 2024Article
- Face the Future-Artificial Intelligence in Oral and Maxillofacial Surgery.Journal of clinical medicine · 2023Review
- Automated cornea diagnosis using deep convolutional neural networks based on cornea topography maps.Scientific reports · 2023Article
- DICOM in Dermoscopic Research: an Experience Report and a Way Forward.Journal of digital imaging · 2021Article
- Multispecialty Enterprise Imaging Workgroup Consensus on Interactive Multimedia Reporting Current State and Road to the Future: HIMSS-SIIM Collaborative White Paper.Journal of digital imaging · 2021Review
- A patient-centric dataset of images and metadata for identifying melanomas using clinical context.Scientific data · 2021Article
- The Future of Precision Prevention for Advanced Melanoma.Frontiers in medicine · 2021Article
- Human surface anatomy terminology for dermatology: a Delphi consensus from the International Skin Imaging Collaboration.Journal of the European Academy of Dermatology and Venereology : JEADV · 2020Article
- The Role of DICOM in Artificial Intelligence for Skin Disease.Frontiers in medicine · 2020Article
- Digital Imaging and Communications in Medicine Whole Slide Imaging Connectathon at Digital Pathology Association Pathology Visions 2017.Journal of pathology informatics · 2018Article
- Clinical Perspective of 3D Total Body Photography for Early Detection and Screening of Melanoma.Frontiers in medicine · 2018Article
- HI-MViT: A lightweight model for explainable skin disease classification based on modified MobileViT.Digital healthArticle
- Artificial Intelligence: How is It Changing Medical Sciences and Its Future?Indian journal of dermatologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
Abstract
Imaging is increasingly being used in dermatology for documentation, diagnosis, and management of cutaneous disease. The lack of standards for dermatologic imaging is an impediment to clinical uptake. Standardization can occur in image acquisition, terminology, interoperability, and metadata. This paper presents the International Skin Imaging Collaboration position on standardization of metadata for dermatologic imaging. Metadata is essential to ensure that dermatologic images are properly managed and interpreted. There are two standards-based approaches to recording and storing metadata in dermatologic imaging. The first uses standard consumer image file formats, and the second is the file format and metadata model developed for the Digital Imaging and Communication in Medicine (DICOM) standard. DICOM would appear to provide an advantage over using consumer image file formats for metadata as it includes all the patient, study, and technical metadata necessary to use images clinically. Whereas, consumer image file formats only include technical metadata and need to be used in conjunction with another actor-for example, an electronic medical record-to supply the patient and study metadata. The use of DICOM may have some ancillary benefits in dermatologic imaging including leveraging DICOM network and workflow services, interoperability of images and metadata, leveraging existing enterprise imaging infrastructure, greater patient safety, and better compliance to legislative requirements for image retention.
Indexed as
Identifiers
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.