DrFinneas Catling

I am an Academic Critical Care doctor. My research aims at improved diagnosis and personalised treatment of critical illness, using methods from Bayesian statistics and machine learning. I am particularly interested in merging these methods with physiological models to provide bedside decision support, in disease heterogeneity, and in the role of uncertainty in clinical decision-making.

In 2020 I was awarded a Wellcome Trust Clinical PhD Fellowship at Imperial, supervised by Prof Anthony Gordon and Dr Steve Harris. During my PhD, I made novel contributions to our understanding of sepsis haemodynamics, and produced a system for treatment personalisation in septic shock (based on Bayesian inversion of a one-dimensional cardiovascular model) using the arterial pressure waveform.

My previous work includes uncertainty-aware mortality risk prediction for patients undergoing emergency laparotomy, representing ICU patients’ status using time-series data to predict clinical events, using structured knowledge for automated clinical coding and phenotyping ventilator-associated pneumonia in electronic health records.

I am an NHS England Clinical Entrepreneurship Fellow and a fellow of the British Computer Society. I co-founded and lecture on the Data Science for Doctors courses, and previously co-founded the medical education startup T-Log.

See my ResearchGate, Twitter or LinkedIn profiles for more information, or get in touch via email.

For my open-source software (including medical-waveforms, a Python library for preprocessing and analysis of physiological waveforms), please see my GitHub profile.