A Hybrid AI Framework for Sensor-Based Personal Health Monitoring towards Precision Health

Authors

  • Mbithe Nzomo University of Cape Town

DOI:

https://doi.org/10.1609/aaai.v38i21.30403

Keywords:

Health Monitoring, Sensor Data, Agent Architecture, Neuro-symbolic AI

Abstract

Non-communicable diseases are on the rise globally, resulting in accelerated efforts to develop personal health monitoring systems for early detection, prediction, and prevention of diseases. This is part of the vision of precision health, an emerging paradigm that focuses on preventing disease before it strikes by encouraging people to actively monitor and work towards improving their health. A key facilitator of this is the use of wearable sensors that can collect and measure physiological data.Although many sensor-based health monitoring systems have been proposed, interoperability of health data and processes, prediction of future health states, and uncertainty management remain open challenges. This research aims to alleviate these challenges through the development of a reusable framework integrating both data-driven and knowledge-driven AI within a hybrid AI architecture.

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Published

2024-03-24

How to Cite

Nzomo, M. (2024). A Hybrid AI Framework for Sensor-Based Personal Health Monitoring towards Precision Health. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23405-23406. https://doi.org/10.1609/aaai.v38i21.30403