One of our clinicians in the CDT, Allan Pang, presented his work on ML-driven physiological early warning systems this summer at the Machine Learning for Healthcare Conference at Colombia University, New York City. As the name suggests, this conference lies at the intersection of ML and Healthcare to encourage collaboration between clinicians and ML practitioners. Some take-home reflections following the meeting are the need to consider the broader systemic effect that the ML model will have once implemented rather than just the traditional data-centric metrics. For instance, a positive change in healthcare behaviour is more critical than increasing application engagement. This approach requires a clear definition of the problem that needs solving and clear metrics to monitor progress. If we fail to do this, this can lead to blind optimisation and unforeseen consequences for patients and healthcare staff alike. Of course, not one to miss the opportunity to combine a run and sightseeing, the weather allowed for a Sunday morning run across the Brooklyn and Manhattan bridges to admire the New York skyline!

Blog written by: Allan Pang