Evidence map›Paper›PMID 28841416›Full record

ReviewCell2017

High-Definition Medicine.

Ali Torkamani, Kristian G Andersen, Steven R Steinhubl, Eric J Topol

Abstract readReview
In one paragraph

Review in Cell, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
98citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

98 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Longitudinal big biological data in the AI era.Molecular systems biology · 2025
    Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. Review
  17. Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025
    Review
  18. Article
  19. Review
  20. Review

38 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ali TorkamaniThe Scripps Translational Science Institute, La Jolla, CA 92037, USA; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA. Electronic address: atorkama@scripps.edu.
Kristian G AndersenThe Scripps Translational Science Institute, La Jolla, CA 92037, USA; Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, CA 92037, USA.
Steven R SteinhublThe Scripps Translational Science Institute, La Jolla, CA 92037, USA; Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.
Eric J TopolThe Scripps Translational Science Institute, La Jolla, CA 92037, USA; Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA 92037, USA.

Funding

SCRIPPS TRANSLATIONAL SCIENCE INSTITUTE (UL1)UL1RR025774 · NCRR · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2008 to 2011
$16.3M
TRAININGU54GM114833 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LINDSEY, MERRY L., PING, PEIPEI · 2014 to 2017
$13.8M
Scripps Genome ADVISER: Annotation and Distributed Variant Interpretation SERverU01HG006476 · NHGRI · SCRIPPS HEALTH · PI TORKAMANI, ALI · 2012 to 2015
$1.1M
NCRR NIH HHS UL1 RR025774NHGRI NIH HHS U01 HG006476NIGMS NIH HHS U54 GM114833
6 · The paper itself

Abstract

The foundation for a new era of data-driven medicine has been set by recent technological advances that enable the assessment and management of human health at an unprecedented level of resolution-what we refer to as high-definition medicine. Our ability to assess human health in high definition is enabled, in part, by advances in DNA sequencing, physiological and environmental monitoring, advanced imaging, and behavioral tracking. Our ability to understand and act upon these observations at equally high precision is driven by advances in genome editing, cellular reprogramming, tissue engineering, and information technologies, especially artificial intelligence. In this review, we will examine the core disciplines that enable high-definition medicine and project how these technologies will alter the future of medicine.

Indexed as

Datasets as TopicDiseaseEnvironmental MonitoringFitness TrackersGenetic EngineeringGenetic Predisposition to DiseaseGenome, HumanHealth SurveysHumansNutrition AssessmentPrecision Medicine

Identifiers

PMID28841416
PMCPMC5714316

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.