[2301.11146] Two-step interpretable modeling of Intensive Care Acquired Infections

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Obtain a PDF of the paper titled Two-step interpretable modeling of Intensive Care Acquired Infections, by Giacomo Lancia and three different authors

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Summary:We current a novel methodology for integrating excessive decision longitudinal knowledge with the dynamic prediction capabilities of survival fashions. The purpose is two-fold: to enhance the predictive energy whereas sustaining interpretability of the fashions. To transcend the black field paradigm of synthetic neural networks, we suggest a parsimonious and strong semi-parametric method (i.e., a landmarking competing dangers mannequin) that mixes routinely collected low-resolution knowledge with predictive options extracted from a convolutional neural community, that was skilled on excessive decision time-dependent data. We then use saliency maps to research and clarify the additional predictive energy of this mannequin. As an instance our methodology, we give attention to healthcare-associated infections in sufferers admitted to an intensive care unit.

Submission historical past

From: Cristian Spitoni [view email]
[v1]
Thu, 26 Jan 2023 14:54:17 UTC (6,116 KB)
[v2]
Wed, 6 Mar 2024 13:46:06 UTC (6,901 KB)



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