Bryan P Weichelt, Matthew Pilz, Richard Burke, David Puthoff, Kang Namkoong
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引用次数: 0
Abstract
Generative Artificial Intelligence (AI) provides unprecedented opportunities to improve injury surveillance systems in many ways, including the curation and publication of information related to agricultural injuries and illnesses. This editorial explores the feasibility and implication of ChatGPT integration in an international sentinel agricultural injury surveillance system, AgInjuryNews, highlighting that AI integration may enhance workflows by reducing human and financial resources and increasing outputs. In the coming years, text intensive natural language reports in AgInjuryNews and similar systems could be a rich source for data for ChatGPT or other more customized and fine-tuned LLMs. By harnessing the capabilities of AI and NLP, teams could potentially streamline the process of data analysis, report generation, and public dissemination, ultimately contributing to improved agricultural injury prevention efforts, well beyond any manually driven efforts.
期刊介绍:
The Journal of Agromedicine: Practice, Policy, and Research publishes translational research, reports and editorials related to agricultural health, safety and medicine. The Journal of Agromedicine seeks to engage the global agricultural health and safety community including rural health care providers, agricultural health and safety practitioners, academic researchers, government agencies, policy makers, and others. The Journal of Agromedicine is committed to providing its readers with relevant, rigorously peer-reviewed, original articles. The journal welcomes high quality submissions as they relate to agricultural health and safety in the areas of:
• Behavioral and Mental Health
• Climate Change
• Education/Training
• Emerging Practices
• Environmental Public Health
• Epidemiology
• Ergonomics
• Injury Prevention
• Occupational and Industrial Health
• Pesticides
• Policy
• Safety Interventions and Evaluation
• Technology