Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study.
Nicola Luigi BragazziGuglielmo DiniAlessandra ToletoneFrancesco BrigoPaolo DurandoPublished in: PloS one (2016)
GT could be useful to assess the reaction of the public and the level of public engagement both to novel risk-factors associated to occupational diseases, and possibly related changes in disease natural history, and to the effectiveness of preventive workplace practices and legislative measures adopted to improve occupational health. Further, occupational clinicians should become aware of the topics most frequently searched by patients and proactively address these concerns during the medical examination. Institutional bodies and organisms should be more present and active in digital tools and media to disseminate and communicate scientifically accurate information. This manuscript should be intended as preliminary, exploratory communication, paving the way for further studies.
Keyphrases
- healthcare
- big data
- mental health
- risk factors
- end stage renal disease
- artificial intelligence
- machine learning
- ejection fraction
- chronic kidney disease
- randomized controlled trial
- public health
- newly diagnosed
- primary care
- prognostic factors
- emergency department
- palliative care
- high resolution
- electronic health record
- peritoneal dialysis
- multidrug resistant
- gram negative
- data analysis
- drug induced
- pulmonary fibrosis
- affordable care act