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Item Leveraging AI in Advancing Public Health Officers’ Practice in Sanitary Premise Inspection: A Demonstrative Study.(Daystar University, Global Cybershield., 2024) Odero, Collince OmondiIn Kenya, the public health profession faces several challenges which contribute to noncompliance with public health requirements. Artificial intelligence (AI) tools have become popular in the country, such as ChatGPT which can be accessed by the public, including public health officers. ChatGPT can leverage public health activities and improve the outcomes and practice competence during premise inspections. This study aims to examine AI’s role in advancing public health officers’ practice with a focus on premise inspection. This study employs the demonstration method where the generative AI tool, ChatGPT, will be used to 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 replies from ChatGPT 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 both the community level (premise owners, general public) and professional level (public health officers, health structure, health service tiers). This is because it can generate trustworthy suggestions for compliance with premise inspection requirements 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 ChatGPT in public health inspections.Item Localized AI-Driven Remote Monitoring and Predictive Analytics to Enhance Maternal Health in Rural Kenya: Bridging Accessibility and High-Risk Pregnancy Management(Daystar University, Global Cybershield Conference, 2024) Oburu, Jeffar J.; Simwa, Richard OnyinoMaternal health services in rural Kenya face significant challenges including limited access to healthcare facilities, a shortage of trained healthcare personnel, and inadequate monitoring of high-risk pregnancies. These factors contribute to high maternal and infant mortality rates. Current advancements in AI offer a potential solution to these issues, yet their application in this specific context remains underexplored. This study aims to fill this gap by developing a localized AI-driven remote monitoring system that utilizes predictive analytics for early detection and continuous management of high-risk pregnancies. This system will be integrated with a mobile health (mHealth) application designed to disseminate crucial health information and reminders to expectant mothers. The primary objective is to enhance maternal health outcomes by leveraging advanced AI technologies tailored to the local context of rural Kenya. The research will begin with a needs assessment through surveys and focus group discussions with local healthcare providers and expectant mothers to identify specific challenges and requirements. Based on these insights, a localized AI-driven remote monitoring system will be developed to track high-risk pregnancies, while predictive analytics will be employed to forecast potential complications. Additionally, the mHealth application will provide critical health information and timely reminders. The effectiveness of these interventions will be evaluated using a quasi-experimental design, comparing maternal and infant mortality rates, healthcare accessibility, and user satisfaction between intervention and control groups. This research aims to demonstrate the transformative potential of AI in addressing maternal health challenges in rural Kenya, offering a scalable model for similar regions globally. Anticipated outcomes include reduced maternal and infant mortality rates, improved healthcare access, and enhanced delivery of maternal health services.