Evidence map›Paper›PMID 29400354›Full record

ArticleComputational psychiatry (Cambridge, Mass.)2017

Computational Nosology and Precision Psychiatry.

Karl J Friston, A David Redish, Joshua A Gordon

Abstract read
In one paragraph

Article in Computational psychiatry (Cambridge, Mass.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.

0numbers the graph read from it
0cells of the map it votes in
71citing 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

71 citing papers in PubMed.

  1. Trial
  2. Trial
  3. The Free Energy Principle and Free Markets.Entropy (Basel, Switzerland) · 2026
    Article
  4. Article
  5. Article
  6. Review
  7. [Formula: see text] Data-driven profiles of behavior in pediatric medical disorders.Child neuropsychology : a journal on normal and abnormal development in childhood and adolescence · 2026
    Article
  8. Article
  9. Article
  10. Epileptiform Activity and Seizure Risk Follow Long-Term Non-Linear Attractor Dynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Linking fast and slow: The case for generative models.Network neuroscience (Cambridge, Mass.) · 2024
    Review
  16. Article
  17. Article
  18. Uncovering psychiatric phenotypes using unsupervised machine learning: A data-driven symptoms approach.European psychiatry : the journal of the Association of European Psychiatrists · 2023
    Article
  19. Predicting treatment outcome in depression: an introduction into current concepts and challenges.European archives of psychiatry and clinical neuroscience · 2023
    Review
  20. Article

11 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

3 authors.

Karl J FristonThe Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, London WC1N 3BG, UK.
A David RedishDepartment of Neuroscience, University of Minnesota, Minneapolis, MN 55455.
Joshua A GordonDepartment of Psychiatry, Columbia University, New York, NY 10032.

Funding

Wellcome Trust 088130
6 · The paper itself

Abstract

This article provides an illustrative treatment of psychiatric morbidity that offers an alternative to the standard nosological model in psychiatry. It considers what would happen if we treated diagnostic categories not as

Indexed as

Bayesiandynamicsmodel selectionnosologypathophysiologypsychiatrypsychopathologytherapy

Identifiers

PMID29400354
PMCPMC5774181

What OpenQuestion holds

Textmetadata
LicenceTDM
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.