Intracranial hematoma detection and patient transport decision-making

Traumatic intracranial hematomas represent a critical clinical situation where early detection and management are of utmost importance.

Machine learning has been recently used in the detection of neuroradiological findings. Hence, it can be used in the detection of intracranial hematomas and furtherly initiate a management cascade of patient transfer, diagnostics, admission, and emergency intervention.

A diagnostic tool was developed based on artificial intelligence to detect hematomas instantaneously, and automatically start a cascade of actions that support the transfer and management protocol depending on the early diagnosis.