Evidence map›Paper›PMID 27932992›Full record

ArticleFrontiers in physiology2016

Patient Similarity: Emerging Concepts in Systems and Precision Medicine.

Sherry-Ann Brown

Abstract read
In one paragraph

Article in Frontiers in physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
  2. Enhancing diagnostic precision for rare diseases using case-based reasoning.Journal of the American Medical Informatics Association : JAMIA · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. MVASA-HGN: multi-view adaptive semantic-aware heterogeneous graph network forQuantitative imaging in medicine and surgery · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Fine-grained Patient Similarity Measuring using Contrastive Graph Similarity Networks.Proceedings. IEEE International Conference on Healthcare Informatics · 2024
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Artificial intelligence opportunities in cardio-oncology: Overview with spotlight on electrocardiography.American heart journal plus : cardiology research and practice · 2022
    Article
  17. Article
  18. Analyzing Patient Trajectories With Artificial Intelligence.Journal of medical Internet research · 2021
    Article
  19. Patient similarity analytics for explainable clinical risk prediction.BMC medical informatics and decision making · 2021
    Article
  20. 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

1 author.

Sherry-Ann BrownDepartment of Cardiovascular Diseases, Mayo Clinic Rochester, MN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

big data analyticsclinical decision supportcomputational medicinepatient similaritypatient similarity analytics

Identifiers

PMID27932992
PMCPMC5121278

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.