About: ISeeU2: Visually Interpretable ICU mortality prediction using deep learning and free-text medical notes

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About: ISeeU2: Visually Interpretable ICU mortality prediction using deep learning and free-text medical notes Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	ISeeU2: Visually Interpretable ICU mortality prediction using deep learning and free-text medical notes
Creator	Caicedo-Torres, William Gutierrez, Jairo
source	ArXiv
abstract	Accurate mortality prediction allows Intensive Care Units (ICUs) to adequately benchmark clinical practice and identify patients with unexpected outcomes. Traditionally, simple statistical models have been used to assess patient death risk, many times with sub-optimal performance. On the other hand deep learning holds promise to positively impact clinical practice by leveraging medical data to assist diagnosis and prediction, including mortality prediction. However, as the question of whether powerful Deep Learning models attend correlations backed by sound medical knowledge when generating predictions remains open, additional interpretability tools are needed to foster trust and encourage the use of AI by clinicians. In this work we show a Deep Learning model trained on MIMIC-III to predict mortality using raw nursing notes, together with visual explanations for word importance. Our model reaches a ROC of 0.8629 (+/-0.0058), outperforming the traditional SAPS-II score and providing enhanced interpretability when compared with similar Deep Learning approaches.
has issue date	2020-05-19(xsd:dateTime)
has license	arxiv
sha1sum (hex)	43180f7a446ea362f009a9e0fb03baa32c93142d
resource representing a document's title	ISeeU2: Visually Interpretable ICU mortality prediction using deep learning and free-text medical notes
resource representing a document's body	covid:43180f7a446ea362f009a9e0fb03baa32c93142d#body_text
is schema:about of	named entity 'patients' named entity 'simple' named entity 'Corresponding' named entity 'CLINICAL PRACTICE' named entity 'STATISTICAL MODELS' »more»

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