ArticleJournal of medical systems2020
De-Identification of Radiomics Data Retaining Longitudinal Temporal Information.
Article in Journal of medical systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Mind the gap: challenges and future directions for content-based image retrieval in clinical radiology.Frontiers in radiology · 2026Article
- Leveraging large language models for the deidentification and temporal normalization of sensitive health information in electronic health records.NPJ digital medicine · 2025Article
- A Two-Stage De-Identification Process for Privacy-Preserving Medical Image Analysis.Healthcare (Basel, Switzerland) · 2022Article
- Evaluating Quality Indicators of Glioblastoma Care: Audit Results From an Indian Tertiary Care Cancer Center.JCO global oncology · 2022Article
- Research Goal-Driven Data Model and Harmonization for De-Identifying Patient Data in Radiomics.Journal of digital imaging · 2021Article
- Article
- A Corrigendum on "De-Identification of Radiomics Data Retaining Longitudinal Temporal Information".Journal of medical systems · 2020Article
- Letter to the editor of the Journal of Medical Systems: Regarding "De-Identification of Radiomics Data Retaining Longitudinal Temporal Information".Journal of medical systems · 2020Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
We propose a de-identification system which runs in a standalone mode. The system takes care of the de-identification of radiation oncology patient's clinical and annotated imaging data including RTSTRUCT, RTPLAN, and RTDOSE. The clinical data consists of diagnosis, stages, outcome, and treatment information of the patient. The imaging data could be the diagnostic, therapy planning, and verification images. Archival of the longitudinal radiation oncology verification images like cone beam CT scans along with the initial imaging and clinical data are preserved in the process. During the de-identification, the system keeps the reference of original data identity in encrypted form. These could be useful for the re-identification if necessary.
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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.