Evidence map›Paper›PMID 34462315›Full record

ArticleCMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne2021

Evaluation of machine learning solutions in medicine.

Tony Antoniou, Muhammad Mamdani

Abstract readComment
In one paragraph

Article in CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

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

23 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Evaluating artificial intelligence-enabled medical tests in cardiology: Best practice.International journal of cardiology. Heart & vasculature · 2025
    Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Perceptions of Canadian vascular surgeons toward artificial intelligence and machine learning.Journal of vascular surgery cases and innovative techniques · 2022
    Article
  15. Article
  16. Article
  17. Biased data lead to biased algorithms.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2022
    Article
  18. Review
  19. Article
  20. CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Tony AntoniouLi Ka Shing Centre for Healthcare Analytics Research & Training (Antoniou, Mamdani), Unity Health Toronto; Li Ka Shing Knowledge Institute (Antoniou, Mamdani), Unity Health Toronto; Department of Family and Community Medicine (Antoniou), Unity Health Toronto and University of Toronto; Temerty Faculty of Medicine (Mamdani) and Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto; Institute of Health Policy, Management, and Evaluation (Mamdani), University of Toronto, Toronto, Ont. tony.antoniou@unityhealth.to.
Muhammad MamdaniLi Ka Shing Centre for Healthcare Analytics Research & Training (Antoniou, Mamdani), Unity Health Toronto; Li Ka Shing Knowledge Institute (Antoniou, Mamdani), Unity Health Toronto; Department of Family and Community Medicine (Antoniou), Unity Health Toronto and University of Toronto; Temerty Faculty of Medicine (Mamdani) and Leslie Dan Faculty of Pharmacy (Mamdani), University of Toronto; Institute of Health Policy, Management, and Evaluation (Mamdani), University of Toronto, Toronto, Ont.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Machine LearningMedicineHumans

Identifiers

PMID34462315
PMCPMC8443287

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.