Evidence map›Paper›PMID 32318028›Full record

ReviewFrontiers in microbiology2020

The Computational Diet: A Review of Computational Methods Across Diet, Microbiome, and Health.

Ameen Eetemadi, Navneet Rai, Beatriz Merchel Piovesan Pereira, Minseung Kim, Harold Schmitz, Ilias Tagkopoulos

Abstract readReview
In one paragraph

Review in Frontiers in microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

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

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. A Familiar Outbreak of MonophasicPathogens (Basel, Switzerland) · 2022
    Article
  6. Review
  7. Understanding the Formation and Mechanism of Anticipatory Responses inInternational journal of molecular sciences · 2022
    Article
  8. Review
  9. Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
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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

6 authors.

Ameen EetemadiDepartment of Computer Science, University of California, Davis, Davis, CA, United States.
Navneet RaiGenome Center, University of California, Davis, Davis, CA, United States.
Beatriz Merchel Piovesan PereiraGenome Center, University of California, Davis, Davis, CA, United States.
Minseung KimDepartment of Computer Science, University of California, Davis, Davis, CA, United States.
Harold SchmitzGraduate School of Management, University of California, Davis, Davis, CA, United States.
Ilias TagkopoulosDepartment of Computer Science, University of California, Davis, Davis, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food and human health are inextricably linked. As such, revolutionary impacts on health have been derived from advances in the production and distribution of food relating to food safety and fortification with micronutrients. During the past two decades, it has become apparent that the human microbiome has the potential to modulate health, including in ways that may be related to diet and the composition of specific foods. Despite the excitement and potential surrounding this area, the complexity of the gut microbiome, the chemical composition of food, and their interplay

Indexed as

artificial intelligencedata analyticsgut microbiomemachine learningmicrobiotanutrition

Identifiers

PMID32318028
PMCPMC7146706

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.