Evidence map›Paper›PMID 28377724›Full record

ArticleFrontiers in physiology2017

Toward Precision Healthcare: Context and Mathematical Challenges.

Caroline Colijn, Nick Jones, Iain G Johnston, Sophia Yaliraki, Mauricio Barahona

Abstract read
In one paragraph

Article in Frontiers in physiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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

15 citing papers in PubMed.

  1. Sorting out and navigating uncertainty in precision medicine.History and philosophy of the life sciences · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Evolving mtDNA populations within cells.Biochemical Society transactions · 2019
    Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Big Data's Role in Precision Public Health.Frontiers in public health · 2018
    Review
  14. Article
  15. Article
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

5 authors.

Caroline ColijnDepartment of Mathematics, Imperial College LondonLondon, UK; EPSRC Centre for Mathematics of Precision Healthcare, Imperial College LondonLondon, UK.
Nick JonesDepartment of Mathematics, Imperial College LondonLondon, UK; EPSRC Centre for Mathematics of Precision Healthcare, Imperial College LondonLondon, UK.
Iain G JohnstonEPSRC Centre for Mathematics of Precision Healthcare, Imperial College LondonLondon, UK; School of Biosciences, University of BirminghamBirmingham, UK.
Sophia YalirakiEPSRC Centre for Mathematics of Precision Healthcare, Imperial College LondonLondon, UK; Department of Chemistry, Imperial College LondonLondon, UK.
Mauricio BarahonaDepartment of Mathematics, Imperial College LondonLondon, UK; EPSRC Centre for Mathematics of Precision Healthcare, Imperial College LondonLondon, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision medicine refers to the idea of delivering the right treatment to the right patient at the right time, usually with a focus on a data-centered approach to this task. In this perspective piece, we use the term "precision healthcare" to describe the development of precision approaches that bridge from the individual to the population, taking advantage of individual-level data, but also taking the social context into account. These problems give rise to a broad spectrum of technical, scientific, policy, ethical and social challenges, and new mathematical techniques will be required to meet them. To ensure that the science underpinning "precision" is robust, interpretable and well-suited to meet the policy, ethical and social questions that such approaches raise, the mathematical methods for data analysis should be transparent, robust, and able to adapt to errors and uncertainties. In particular, precision methodologies should capture the complexity of data, yet produce tractable descriptions at the relevant resolution while preserving intelligibility and traceability, so that they can be used by practitioners to aid decision-making. Through several case studies in this domain of precision healthcare, we argue that this vision requires the development of new mathematical frameworks, both in modeling and in data analysis and interpretation.

Indexed as

data sciencemathematical modelingprecision healthcareprecision medicineprecision public health

Identifiers

PMID28377724
PMCPMC5359292

What OpenQuestion holds

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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.