ReviewNature genetics2020
Treating medical data as a durable asset.
Review in Nature genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 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
13 citing papers in PubMed.
- Generative AI Chatbots Could Take Over Our Emotional Lives: The Potential and Challenges of Generative AI for Health Globally.Clinical psychology in Europe · 2026Article
- Combining Real and Synthetic Data to Overcome Limited Training Datasets in Multimodal Learning.medRxiv : the preprint server for health sciences · 2025Article
- Morbidity of SARS-CoV-2 in the evolution to endemicity and in comparison with influenza.Communications medicine · 2024Article
- Potential Benefits of Non-Fungible Tokens (NFTs) and Blockchain Technology in Dermatology.Dermatology practical & conceptual · 2024Article
- Semantic wikis as flexible database interfaces for biomedical applications.Scientific reports · 2023Article
- Translational Bioinformatics for Human Reproductive Biology Research: Examples, Opportunities and Challenges for a Future Reproductive Medicine.International journal of molecular sciences · 2022Review
- Short Chain Fatty Acid Metabolism in Relation to Gut Microbiota and Genetic Variability.Nutrients · 2022Review
- EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation.BMC bioinformatics · 2022Article
- Federated learning algorithms for generalized mixed-effects model (GLMM) on horizontally partitioned data from distributed sources.BMC medical informatics and decision making · 2022Article
- SVAT: Secure outsourcing of variant annotation and genotype aggregation.BMC bioinformatics · 2022Article
- Who Will Get Paid for Artificial Intelligence in Medicine?Radiology. Artificial intelligence · 2022Article
- Alliance chain-based simulation on a new clinical research data pricing model.Annals of translational medicine · 2022Article
- Development and application of a healthcare data quality indicator framework from the perspective of data-as-a-product.Digital healthArticle
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Access to medical data is central for conducting research on genomics. However, to tap these metadata (observable traits and phenotypes, diagnoses and medication, and labels), researchers must grapple with the complex and sensitive nature of the information. In this Perspective, we argue that, at this exciting time for genomics and artificial intelligence, several critical aspects of data generation, infrastructure and management are pillars of a modern data ecosystem. Many risks to privacy and many obstacles to medical research can be eliminated or mitigated by new secure data analytics. Finally, we discuss the potential consequences of medical data exiting the institutions and being managed by individuals. These shifts in data ownership have the potential for profound disruption and opportunity across many fields.
Indexed as
Identifiers
32929286What 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.