ArticleNature medicine2021
Personalized lab test models to quantify disease potentials in healthy individuals.
Article in Nature medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
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- Classifying smoking status using linear and non-linear models based on clinical health records.Analytical and bioanalytical chemistry · 2026Article
- A generalist precision medication framework using temporal causal inference based on treatment-free physiological profiles.Nature communications · 2026Article
- On the genetic origins of phenotypes in genome-wide association studies: the SAFE-hBMC bioinformatics · 2026Article
- Pregnancy lab test dynamics resemble rejuvenation of some organs and aging of others.Nature communications · 2026Article
- An interpretable machine learning model using routine clinical data for early recurrence prediction in hepatocellular carcinoma.Scientific reports · 2026Article
- Subtle Laboratory and Clinical Precursors of Celiac Disease in Young Adults: A Large-Scale Retrospective Cohort Study.Journal of general internal medicine · 2026Article
- Low serum IgE is associated with an increased risk of chronic lymphocytic leukemia: a large retrospective cohort study.Frontiers in immunology · 2026Observational
- Isolated ventricular septal defect is not a risk factor for celiac disease: evidence from a large real-world data cohort of 493,382 children.Frontiers in pediatrics · 2026Article
- Ageing, immune fitness and cancer.Nature reviews. Cancer · 2025Review
- Combining clinical chemistry with metabolomics for metabolic phenotyping at population levels.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- A reference model of circulating hematopoietic stem cells across the lifespan with applications to diagnostics.Nature medicine · 2025Article
- Mapping circulating hematopoietic stem cells for non-invasive, blood-based diagnostics.Nature medicine · 2025Article
- Pregnancy and postpartum dynamics revealed by millions of lab tests.Science advances · 2025Article
- Democratizing precision oncology with SCORPIO.Nature medicine · 2025Article
- Prediction of checkpoint inhibitor immunotherapy efficacy for cancer using routine blood tests and clinical data.Nature medicine · 2025Article
- Haematology dimension reduction, a large scale application to regular care haematology data.BMC medical informatics and decision making · 2025Article
- Article
- Longitudinal machine learning uncouples healthy aging factors from chronic disease risks.Nature aging · 2024Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Standardized lab tests are central for patient evaluation, differential diagnosis and treatment. Interpretation of these data is nevertheless lacking quantitative and personalized metrics. Here we report on the modeling of 2.1 billion lab measurements of 92 different lab tests from 2.8 million adults over a span of 18 years. Following unsupervised filtering of 131 chronic conditions and 5,223 drug-test pairs we performed a virtual survey of lab tests distributions in healthy individuals. Age and sex alone explain less than 10% of the within-normal test variance in 89 out of 92 tests. Personalized models based on patients' history explain 60% of the variance for 17 tests and over 36% for half of the tests. This allows for systematic stratification of the risk for future abnormal test levels and subsequent emerging disease. Multivariate modeling of within-normal lab tests can be readily implemented as a basis for quantitative patient evaluation.
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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.