AORTA-AI: Rapid Acute Aortic Syndrome Diagnosis using Artificial Intelligence

Project Aim

This research aims to develop an AI/ML decision support system that enhances the diagnosis of AAS at the crucial point of hospital presentation. The project will integrate two diverse data sets, involving over 6,000 patients with potential AAS symptoms and those with confirmed AAS diagnoses, to create this decision support system. By using historical data and routinely collected information, the project seeks to provide healthcare professionals with actionable insights for early and appropriate management of AAS, mitigating the risk of death and other complications.

As a proof-of-concept study, this AI tool aims to bolster healthcare professionals’ confidence by revealing subtle diagnostic patterns that may be overlooked by human observation alone. If successful, the AI-based tool could be implemented in emergency departments as a standard screening mechanism for AAS. This would minimise clinical biases and variations in the initial medical assessment, replacing it with a robust AI review for personalised risk assessment and treatment plans. Ultimately, this will improve diagnostic accuracy, reduce instances of missed or incorrect diagnoses, and enhance patient care and outcomes.