ArticleYonsei medical journal2022
Concept and Proof of the Lifelog Bigdata Platform for Digital Healthcare and Precision Medicine on the Cloud.
Article in Yonsei medical journal, 2022. 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
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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.
- Medical Big Data Storage in Precision Medicine: A Systematic Review.Journal of biomedical physics & engineering · 2025Article
- Metaverse and its impact on medical education and health care system: A narrative review.Health science reports · 2024Article
- A machine learning approach using conditional normalizing flow to address extreme class imbalance problems in personal health records.BioData mining · 2024Article
- Development and Validation of a Clinic Machine Learning Classifier for the Prediction of Risk Stratifications of Prostate Cancer Bone Metastasis Progression to Castration Resistance.International journal of general medicine · 2024Article
- Diffusion of a Lifelog-Based Digital Healthcare Platform for Future Precision Medicine: Data Provision and Verification Study.Journal of personalized medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
purposeWe propose the Lifelog Bigdata Platform as a sustainable digital healthcare system based on individual-centric lifelog datasets and describe the standardization of lifelog and clinical data in its full-cycle management system. MATERIALS AND
methodsThe Lifelog Bigdata Platform was developed by Yonsei Wonju Health System on the cloud to support digital healthcare and precision medicine. It consists of five core components: data acquisition system, de-identification of individual information, lifelog integration, analyzer, and service. We designed a gathering system into a dedicated virtual machine to save lifelog or clinical outcomes and established standard guidelines for maintaining the quality of gathering procedures. We used standard integration keys to integrate the lifelog and clinical data. Metadata were generated from the data warehouse after loading combined or fragmented data on it. We analyzed the de-identified lifelog and clinical data using the lifelog analyzer to prevent and manage acute and chronic diseases through providing results of statistics on analysis.
resultsThe big data centers were built in four hospitals and seven companies for integrating lifelog and clinical data to develop the Lifelog Bigdata Platform. We integrated and loaded lifelog big data and clinical data for 3 years. In the first year, we uploaded 94 types of data on the platform with a total capacity of 221 GB.
conclusionThe Lifelog Bigdata Platform is the first to combine lifelog and clinical data. The proposed standardization guidelines can be used for future platforms to achieve a virtuous cycle structure of lifelogging big data and an industrial ecosystem.
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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.