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arXiv · 2301.08019

Identification, explanation and clinical evaluation of hospital patient subtypes

Enrico Werner·Jeffrey N. Clark·Ranjeet S. Bhamber·Michael Ambler·Christopher P. Bourdeaux·Alexander Hepburn·Christopher J. McWilliams·Raul Santos-Rodriguez
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Abstract

We present a pipeline in which unsupervised machine learning techniques are used to automatically identify subtypes of hospital patients admitted between 2017 and 2021 in a large UK teaching hospital. With the use of state-of-the-art explainability techniques, the identified subtypes are interpreted and assigned clinical meaning. In parallel, clinicians assessed intra-cluster similarities and inter-cluster differences of the identified patient subtypes within the context of their clinical knowledge. By confronting the outputs of both automatic and clinician-based explanations, we aim to highlight the mutual benefit of combining machine learning techniques with clinical expertise.

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Enrico Werner, Jeffrey N. Clark, Ranjeet S. Bhamber, Michael Ambler, Christopher P. Bourdeaux, Alexander Hepburn, Christopher J. McWilliams, Raul Santos-Rodriguez. 2023-01-19. Identification, explanation and clinical evaluation of hospital patient subtypes. https://arxiv.org/abs/2301.08019

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