Tracking population geography when training AI models for healthcare is highly beneficial as it allows the AI to understand and adapt to regional health trends and disparities. This geographical data ensures the AI models are tailored to provide accurate predictions and recommendations, reflecting the specific health needs and conditions of different populations.

The relationship between location and Health Population is essential for training AI models. A single location may train multiple AI models using different Health Populations. Similarly, one location might support various Health Populations for AI training. Moreover, several locations could contribute to train a single AI model. Each combination of location, Health Population, and AI is unique within the dataset, serving as the identification scheme for Location-Health-Population-AI-Training.

Based on the “Final Report of the Roundtable on Artificial Intelligence in Healthcare” Final-Report-of-the-Roundtable-on-Artificial-Intelligence-in-Healthcare.pdf