This article presents a novel method, called Modular Grammatical Evolution (MGE), toward validating the hypothesis that restricting the solution space of NeuroEvolution to modular and simple neural networks enables the efficient generation of smaller...
OBJECTIVE: Vital signs and laboratory values are used to guide decisions to use damage control techniques in lieu of early definitive fracture fixation. Previous models attempted to predict mortality risk but have limited utility. There is a need for...
In the quest to understand how structure and dynamics are connected in glasses, a number of machine learning based methods have been developed that predict dynamics in supercooled liquids. These methods include both increasingly complex machine learn...
BACKGROUND: Machine learning (ML) methodology development for the classification of immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of sc...
Studies in health technology and informatics
May 25, 2022
Methods of natural language processing associated with machine learning or deep learning can support detection of adverse drug reactions in abstracts of case reports available on Pubmed. In 2012, Gurulingappa et al. proposed a training set for the re...
Studies in health technology and informatics
May 25, 2022
Many medical narratives are read by care professionals in their preferred language. These documents can be produced by organizations, authorities or national publishers. However, they are often hardly findable using the usual query engines based on E...
Studies in health technology and informatics
May 25, 2022
Standardized fall risk scores have not proven to reliably predict falls in clinical settings. Machine Learning offers the potential to increase the accuracy of such predictions, possibly vastly improving care for patients at high fall risks. We devel...
Studies in health technology and informatics
May 25, 2022
Decision support tools in healthcare require a strong confidence in the developed Machine Learning (ML) models both in terms of performances and in their ability to provide users a deeper understanding of the underlying situation. This study presents...
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