ArticleLa Medicina del lavoro2019
Big Data in occupational medicine: the convergence of -omics sciences, participatory research and e-health.
Article in La Medicina del lavoro, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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.
Who cites it
4 citing papers in PubMed.
- Precision prevention in occupational health: a conceptual analysis and development of a unified understanding and an integrative framework.Frontiers in public health · 2024Article
- Big Data for Biomedical Education with a Focus on the COVID-19 Era: An Integrative Review of the Literature.International journal of environmental research and public health · 2021Review
- Gynecology Meets Big Data in the Disruptive Innovation Medical Era: State-of-Art and Future Prospects.International journal of environmental research and public health · 2021Review
- How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic.International journal of environmental research and public health · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNew occupational hazards and risks are emerging in our progressively globalized society, in which ageing, migration, wild urbanization and rapid economic growth have led to unprecedented biological, chemical and physical exposures, linked to novel technologies, products and duty cycles. A focus shift from worker health to worker/citizen and community health is crucial. One of the major revolutions of the last decades is the computerization and digitization of the work process, the so-called "work 4.0", and of the workplace.
objectivesTo explore the roles and implications of Big Data in the new occupational medicine settings.
methodsComprehensive literature search.
resultsBig Data are characterized by volume, variety, veracity, velocity, and value. They come both from wet-lab techniques ("molecular Big Data") and computational infrastructures, including databases, sensors and smart devices ("computational Big Data" and "digital Big Data").
conclusionsIn the light of novel hazards and thanks to new analytical approaches, molecular and digital underpinnings become extremely important in occupational medicine. Computational and digital tools can enable us to uncover new relationships between exposures and work-related diseases; to monitor the public reaction to novel risk factors associated to occupational diseases; to identify exposure-related changes in disease natural history; and to evaluate preventive workplace practices and legislative measures adopted for workplace health and safety.
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What OpenQuestion holds
Registered trials
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.