Home⇛Recoletos Multidisciplinary Research Journal⇛vol. 1 no. Special Issue (2025)

Pitik: A Cebuano-Binisaya Intent-Based Chatbot for Cardiovascular Disease Patient Profiling and Risk Factor Recommendations

Joseph Cedeño | Andrew Manteza | Nicole Nacar | Merhamdin Umbukan | Cherrie Muaña | Ma. Juliet Vasay-cruz | Ceasar Ian P. Benablo | Kristine Mae Adlaon

Discipline: health studies

 

Abstract:

Background: Cardiovascular diseases (CVDs) remain the leading cause of death in the Philippines, affecting one in six Filipinos and accounting for 20% of all deaths. Despite the existence of community-based healthcare programs, patient profiling continues to be done manually, resulting in inefficiencies in cardiovascular risk assessment. To address this, Pitik, a Cebuano-Binisaya intent-based chatbot, was developed to streamline cardiovascular risk profiling and data collection, particularly in underserved areas. Methods: This study collaboratively employed Action Research to refine Pitik through three software development iterations. The chatbot integrated the Diag-Ex framework alongside Pre-Intent and Post-Intent Matching algorithms. Gricean Maxims guided its conversational design to enhance communication accuracy and user interaction quality. Results: The iterative development process significantly improved Pitik's accuracy, reduced communication errors, and increased user engagement. Evaluations demonstrated the chatbot's effectiveness in processing user inputs and providing structured cardiovascular risk assessments. These improvements highlight Pitik's growing capability in delivering accessible and reliable health information. Conclusion: Pitik presents a scalable and linguistically inclusive AI solution for cardiovascular risk assessment within Cebuano-Binisaya-speaking communities. The study underscores the potential of AI-driven chatbots to enhance community-based patient profiling, reduce manual workloads, and improve healthcare access in rural areas. Future work will involve expanding Pitik's features and evaluating its real-world impact in broader healthcare contexts.



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