Haemodynamic profiling: when AI tells us what we already know

Machine learning (ML) algorithms hold significant potential for extracting valuable clinical information from big data, surpassing the processing capabilities of the human brain. However, it would be naïve to believe that ML algorithms can consistently transform data into actionable insights. Clinical studies suggest that in some instances, they tell clinicians what they already know or can plainly see. Additionally, ML algorithms might not be necessary for analysing ‘small data’, such as a limited number of haemodynamic variables. In this respect, whether haemodynamic profiling with an ML algorithm offers advantages over straightforward classification tables or simple visual decision support tools remains unclear.