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Sepsis

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Predicting sepsis with a recurrent neural network using the MIMIC III database.

Computers in biology and medicine
OBJECTIVE: Predicting sepsis onset with a recurrent neural network and performance comparison with InSight - a previously proposed algorithm for the prediction of sepsis onset.

An intelligent warning model for early prediction of cardiac arrest in sepsis patients.

Computer methods and programs in biomedicine
BACKGROUND: Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early prediction of cardiac arrest can provide the time required for intervening and preventing its onset in order to reduce mortality. Several studies have be...

Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs.

Computers in biology and medicine
OBJECTIVE: Sepsis remains a costly and prevalent syndrome in hospitals; however, machine learning systems can increase timely sepsis detection using electronic health records. This study validates a gradient boosted ensemble machine learning tool for...

Refining humane endpoints in mouse models of disease by systematic review and machine learning-based endpoint definition.

ALTEX
Ideally, humane endpoints allow for early termination of experiments by minimizing an animal's discomfort, distress and pain, while ensuring that scientific objectives are reached. Yet, lack of commonly agreed methodology and heterogeneity of cut-off...

Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data.

PloS one
BACKGROUND: Rapid antibiotic administration is known to improve sepsis outcomes, however early diagnosis remains challenging due to complex presentation. Our objective was to develop a model using readily available electronic health record (EHR) data...

An attention based deep learning model of clinical events in the intensive care unit.

PloS one
This study trained long short-term memory (LSTM) recurrent neural networks (RNNs) incorporating an attention mechanism to predict daily sepsis, myocardial infarction (MI), and vancomycin antibiotic administration over two week patient ICU courses in ...

Improving Prediction Performance Using Hierarchical Analysis of Real-Time Data: A Sepsis Case Study.

IEEE journal of biomedical and health informatics
This paper presents a novel method for hierarchical analysis of machine learning algorithms to improve predictions of at risk patients, thus further enabling prompt therapy. Specifically, we develop a multi-layer machine learning approach to analyze ...

Development and Evaluation of a Machine Learning Model for the Early Identification of Patients at Risk for Sepsis.

Annals of emergency medicine
STUDY OBJECTIVE: The Third International Consensus Definitions (Sepsis-3) Task Force recommended the use of the quick Sequential [Sepsis-related] Organ Failure Assessment (qSOFA) score to screen patients for sepsis outside of the ICU. However, subseq...