Deep continual learning for medical call incidents text classification under the presence of dataset shifts

Ferri, Pablo; Lomonaco, Vincenzo; Passaro, Lucia C.; Félix-De Castro, Antonio; Sánchez-Cuesta, Purificación; Sáez, Carlos; García-Gómez, Juan M.

doi:10.1016/j.compbiomed.2024.108548

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Cited by 3 publications

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Leveraging AI technology for distinguishing Eucommiae Cortex processing levels and evaluating anti-fatigue potential

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Exploring the Trade-Off between generalist and specialized Models: A center-based comparative analysis for glioblastoma segmentation

Javier Gil-Terrón,

Ferri,

Montosa-i-Micó

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International Journal of Medical Informatics

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Deep continual multitask out-of-hospital incident severity assessment from changing clinical features

Ferri,

Sáez,

Félix-De Castro

et al. 2024

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When developing Machine Learning models to support emergency medical triage, it is important to consider how changes over time in the data can negatively affect the models' performance. The objective of this study was to assess the effectiveness of novel Deep Continual Learning pipelines in maximizing model performance when input features are subject to change over time, including the emergence of new features and the disappearance of existing ones. The model is designed to identify life-threatening situations, calculate its admissible response delay, and determine its institutional jurisdiction. We analyzed a total of 1 414 575 events spanning from 2009 to 2019. Our findings demonstrate important performance improvements, up to 4.9% in life-threatening, 18.5% in response delay and 1.7% in jurisdiction, in absolute F1-score, compared to the current triage protocol, and improvements up to 4.4% in life-threatening and 11% in response delay, in absolute F1-score, respect to non-continual approaches.

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Deep continual learning for medical call incidents text classification under the presence of dataset shifts

Cited by 3 publications

References 24 publications

Leveraging AI technology for distinguishing Eucommiae Cortex processing levels and evaluating anti-fatigue potential

Leveraging AI technology for distinguishing Eucommiae Cortex processing levels and evaluating anti-fatigue potential

Exploring the Trade-Off between generalist and specialized Models: A center-based comparative analysis for glioblastoma segmentation

Deep continual multitask out-of-hospital incident severity assessment from changing clinical features

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