AI-Based Health Assistant for Young Adults

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https://dl.acm.org/doi/abs/10.1007/978-3-031-93418-6_18

AI-Based Health Assistant for Young Adults

@inproceedings{10.1007/978-3-031-93418-6_18,
author = {Chen, Xin Han and Yu, Boxuan and Fan, Haozheng and Bin Azizan, Muhammad Firdaus and Ong, Chin Ann and Merritt, Timothy and Fernando, Owen Noel Newton},
title = {AI-Based Health Assistant for Young Adults},
year = {2025},
isbn = {978-3-031-93417-9},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
url = {https://doi.org/10.1007/978-3-031-93418-6_18},
doi = {10.1007/978-3-031-93418-6_18},
abstract = {This paper introduces an AI-based health assistant designed to foster healthier eating habits among young adults. Leveraging the Transtheoretical Model (TTM) of behavior change, the system integrates personalized dietary interventions with advanced AI technologies, including a graph-based database and dynamic user interactions powered by ChatGPT. Key features include meal logging, nutrient visualization, and stage-specific recommendations tailored to each user’s progress. A structured evaluation framework lays the foundation for assessing the system’s effectiveness in promoting sustained behavioral improvements. While the current work focuses on short-term outcomes, future enhancements aim to incorporate wearable integrations, gamification, and expanded personalization to address a diverse user base. This research represents a significant step toward harnessing AI to address complex dietary challenges through ethical, user-centric health interventions.},
booktitle = {Artificial Intelligence in HCI: 6th International Conference, AI-HCI 2025, Held as Part of the 27th HCI International Conference, HCII 2025, Gothenburg, Sweden, June 22–27, 2025, Proceedings, Part III},
pages = {263–280},
numpages = {18},
keywords = {AI-based Health Assistant, Transtheoretical Model, Dietary Interventions, Young Adults, ChatGPT, Large Language Models, Neo4j Graph Database, User Engagement},
location = {Gothenburg, Sweden}
}

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