Leveraging Ml and AI in Advancing Public Health Officers’ Practice in Premise Inspection.
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Date
2024
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Daystar University, Global Cybershiled.
Abstract
In Kenya, the public health profession faces several challenges which contribute to noncompliance with public health requirements. Machine learning (ML), and Artificial intelligence (AI) tools have become popular in the country, and globally, such as ChatGPT. ML and AI can leverage public health activities and improve the outcomes and practice competence during premise inspections. This study aims to examine ML and AI’s role in advancing public health officers’ practice with a focus on premise inspection. Digital tools can generate output for premise inspection in various priority areas and compared with contemporary public health practices, and existing public health literature. The key priorities in sanitary premise inspection for compliance with public health to be examined will include sanitary inspection goals, inspection forms, licenses and certificates, and sanitary requirements for food premises. The contextual role of ML and AI will be discussed to establish their relevance to improving public health services in domains such as inspection, checklist development, inspection report writing, and premise compliance with statutory notices among premise owners. AI must be thoughtfully embraced at professional level (public health officers, health structure, health service tiers). This is because it can generate trustworthy suggestions for premise inspection and evade committing public health offences. In this regard, AI can potentially play a role in preventing diseases and promoting health in both urban and rural communities. Recommendations will be provided on limitations encountered and appropriate suggestions given on the potential value or opportunities of ML and Ai in public health inspections.
Description
Conference Paper
Keywords
Public health profession, Machine learning (ML), and Artificial intelligence (AI)
Citation
Odero, C. (2024). Leveraging Ml and AI in Advancing Public Health Officers’ Practice in Premise Inspection. Daystar University, Global Cybershiled.