A NeuroSymbolic Human-in-the-loop Approach Towards Fusing Medical Expert Knowledge with ANNs

At the 21st AIAI 2025 conference, a paper was presented that introduced a novel NeuroSymbolic Human-in-the-loop approach for integrating medical expert knowledge with Artificial Neural Networks (ANNs) in healthcare. This innovative framework combines biometric data from wearable devices with AI models, enabling a collaborative process where both AI and healthcare professionals contribute to model training. The system was evaluated on real-world healthcare datasets, particularly focusing on diabetic patients, and aims to enhance chronic disease management through personalized, AI-driven healthcare solutions.

The paper was part of the 1st Workshop on SilverTech, which explored the potential of AI technologies, including wearable devices and IoT, in improving healthcare for aging populations. While the workshop focused on the integration of these technologies for personalized healthcare, the paper itself highlighted the use of NeuroSymbolic AI for better healthcare prediction, prevention, and intervention, particularly in chronic disease management.