Recent research highlights that longer brain scans significantly enhance the richness of data, leading to better AI predictions and reducing overall research costs.

A comprehensive global study confirms that extending scan durations improves AI model accuracy in brain imaging, making research more cost-effective.

These findings suggest that optimizing data collection by balancing participant numbers and scan length can streamline the development of effective treatments for neurological conditions.

This approach addresses the high expenses traditionally associated with data collection in AI-driven personalized treatments for brain disorders.

The research indicates that scanning fewer individuals for longer periods produces more accurate results than scanning many people for shorter times.