Evidence map›Paper›PMID 38334203›Full record

ReviewJournal of occupational health2024

Artificial intelligence in advancing occupational health and safety: an encapsulation of developments.

Immad A Shah, SukhDev Mishra

Open access · goldAbstract readReview
In one paragraph

Review in Journal of occupational health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
33.8field-weighted citation impact, top 1% of its field
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Observational
  6. Article
  7. Article
  8. Predicting workplace absenteeism using machine learning: a pilot study in occupational health.Journal of occupational medicine and toxicology (London, England) · 2025
    Article
  9. Article
  10. A Novel Macro-Level Model in Evaluating Health and Safety Training Based on Virtual Reality.International journal of environmental research and public health · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Exploring Human-AI Dynamics in Enhancing Workplace Health and Safety: A Narrative Review.International journal of environmental research and public health · 2025
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Update on Occupational Cancer for Better Cancer Prevention and Control.Asian Pacific journal of cancer prevention : APJCP · 2024
    Review
  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

2 authors at 1 institution in 1 country.

Immad A ShahDivision of Health Sciences, ICMR-National Institute of Occupational Health, Ahmedabad, Gujarat, India.
SukhDev MishraDepartment of Biostatistics, Division of Health Sciences, ICMR-National Institute of Occupational Health, Ahmedabad, Gujarat, India.ORCID 0000-0002-0842-1657
National Institute of Occupational Health · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesIn an era characterized by dynamic technological advancements, the well-being of the workforce remains a cornerstone of progress and sustainability. The evolving industrial landscape in the modern world has had a considerable influence on occupational health and safety (OHS). Ensuring the well-being of workers and creating safe working environments are not only ethical imperatives but also integral to maintaining operational efficiency and productivity. We aim to review the advancements that have taken place with a potential to reshape workplace safety with integration of artificial intelligence (AI)-driven new technologies to prevent occupational diseases and promote safety solutions.

methodsThe published literature was identified using scientific databases of Embase, PubMed, and Google scholar including a lower time bound of 1974 to capture chronological advances in occupational disease detection and technological solutions employed in industrial set-ups.

resultsAI-driven technologies are revolutionizing how organizations approach health and safety, offering predictive insights, real-time monitoring, and risk mitigation strategies that not only minimize accidents and hazards but also pave the way for a more proactive and responsive approach to safeguarding the workforce.

conclusionAs industries embrace the transformative potential of AI, a new frontier of possibilities emerges for enhancing workplace safety. This synergy between OHS and AI marks a pivotal moment in the quest for safer, healthier, and more sustainable workplaces.

Indexed as

Occupational DiseasesOccupational HealthArtificial IntelligenceHumansIndustryWorkplaceartificial intelligencemachine learningneural networkoccupational diseasespneumoconiosisworkplace safety

Identifiers

PMID38334203
PMCPMC10878366
OpenAlexW4390547994

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.