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Response to: ‘On using machine learning algorithms to define clinically meaningful patient subgroups’ by Pinal-Fernandez and Mammen

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We have read with interest the comment from Pinal-Fernandez and Mammen in which they question the statistical clustering methods based on unsupervised learning analyses to define clinically meaningful patient subgroups.1… Click to show full abstract

We have read with interest the comment from Pinal-Fernandez and Mammen in which they question the statistical clustering methods based on unsupervised learning analyses to define clinically meaningful patient subgroups.1 Pinal-Fernandez and Mammen base their arguments on the production of an analysis according to this methodology made on a random simulated data set that would highlight the formation of three clusters, in fact arbitrary. It is important to point out that the example which forms the basis of their argument is ill-chosen because it shows a misguided use of this type of technique. Indeed, before applying a clustering method …

Keywords: patient subgroups; meaningful patient; define clinically; pinal fernandez; fernandez mammen; clinically meaningful

Journal Title: Annals of the Rheumatic Diseases
Year Published: 2019

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