<![CDATA[Heatlh conditions can often be detected though external indicators such as fingernails, yet access to rapid expert analysis is frequently a barrier. This research aims to design and build a mobile health application capable of providing automated preliminary analysis of nail conditions using AI techonology. The system integrates a frontend application built with flutter with a backend architecture that utilizes Google Apps Script, Google Sheets as a trigger, and Google Drive for storage. The core functionality relies on an automated workflow built on the n8n platform, which processes user-uploaded nail images through the generative AI model, Google Gemini 1.5 Flash, to produce a visual analysis. The result of this research is a functional and efficient system where users can receive the analysis in the form of an Al-annotated nail image directly on their mobile device. The resulting application was then validated through a series of functional tests to ensure each stage of the automated workflow performed as expected. The testing showed the system successfully processed user input to generate analysis output accurately, thus deeming the application viable for use.]]>
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