ReviewTrends in molecular medicine2023
Opportunities and challenges for biomarker discovery using electronic health record data.
Review in Trends in molecular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Artificial intelligence in drug discovery - what it is, where we stand and the path forward.Nature reviews. Drug discovery · 2026Review
- Influenza vaccination after advanced acute kidney injury: effects on mortality, cardiovascular events, and pneumonia-a target trial emulation.Hypertension research : official journal of the Japanese Society of Hypertension · 2026Article
- Low relative sit-to-stand power in Colombian older adults: Cut-off points and associations with frailty and functional decline.The Journal of frailty & aging · 2026Article
- Artificial intelligence-based biomarkers for the diagnosis and treatment of neurological conditions: a narrative review.Molecular brain · 2026Review
- Generative artificial intelligence in predictive analysis of diabetes and its complications: a narrative review.Annals of translational medicine · 2025Review
- How quantum computing can enhance biomarker discovery.Patterns (New York, N.Y.) · 2025Review
- Polymerase Chain Reaction Chips for Biomarker Discovery and Validation in Drug Development.Micromachines · 2025Review
- Revolutionary Point-of-Care Wearable Diagnostics for Early Disease Detection and Biomarker Discovery through Intelligent Technologies.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection.JMIR medical informatics · 2024Article
- Biases in Electronic Health Records Data for Generating Real-World Evidence: An Overview.Journal of healthcare informatics research · 2024Article
- A state-of-the-art review of functional magnetic resonance imaging technique integrated with advanced statistical modeling and machine learning for primary headache diagnosis.Frontiers in human neuroscience · 2023Review
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.
Funding
Abstract
Electronic health records (EHRs) have become increasingly relied upon as a source for biomedical research. One important research application of EHRs is the identification of biomarkers associated with specific patient states, especially within complex conditions. However, using EHRs for biomarker identification can be challenging because the EHR was not designed with research as the primary focus. Despite this challenge, the EHR offers huge potential for biomarker discovery research to transform our understanding of disease etiology and treatment and generate biological insights informing precision medicine initiatives. This review paper provides an in-depth analysis of how EHR data is currently used for phenotyping and identifying molecular biomarkers, current challenges and limitations, and strategies we can take to mitigate challenges going forward.
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.