Evidence map›Paper›PMID 37634174›Full record

ReviewThe Journal of forensic odonto-stomatology2023

Artificial intelligence in forensic medicine and forensic dentistry.

M Vodanović, M Subašić, D P Milošević, I Galić, H Brkić

Abstract readReview
In one paragraph

Review in The Journal of forensic odonto-stomatology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Interpol review of forensic image and video analysis, 2022-2025.Forensic science international. Synergy · 2026
    Review
  4. Article
  5. Article
  6. Observational
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Review
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.

M VodanovićDepartment of Dental Anthropology, School of Dental Medicine, University of Zagreb, Croatia.
M SubašićFaculty of Electrical Engineering and Computing, University of Zagreb, Croatia.
D P MiloševićFaculty of Electrical Engineering and Computing, University of Zagreb, Croatia.
I GalićSchool of Medicine, University of Split, Croatia.
H BrkićDepartment of Dental Anthropology, School of Dental Medicine, University of Zagreb, Croatia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review article aims to highlight the current possibilities for applying Artificial Intelligence in modern forensic medicine and forensic dentistry and present the advantages and disadvantages of its use. For this purpose, the relevant academic literature was searched using PubMed, Web of Science and Scopus. The application of Artificial Intelligence in forensic medicine and forensic dentistry is still in its early stages. However, the possibilities are great, and the future will show what is applicable in daily practice. Artificial Intelligence will improve the accuracy and efficiency of work in forensic medicine and forensic dentistry; it can automate some tasks; and enhance the quality of evidence. Disadvantages of the application of Artificial Intelligence may be related to discrimination, transparency, accountability, privacy, security, ethics and others. Artificial Intelligence systems should be used as a support tool, not as a replacement for forensic experts.

Indexed as

Artificial IntelligenceForensic DentistryForensic MedicineHumansPrivacyPubMed

Identifiers

PMID37634174
PMCPMC10473456

What OpenQuestion holds

Textmetadata
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.