Article

Deep Learning with Diverse Objectives Improves ARDS Prediction

2021-05-21

Abstract excerpt

When training neural networks (NNs) on time-series inpatient data, as the number of outcomes predicted diversifies, the NN both generalizes better on external validation and reaches higher performance in similar numbers of training epochs. We demonstrated this in the context of predicting decompensation in Acute Respiratory Distress Syndrome (ARDS). The NN outperformed gradient boosted trees, achieving an area und...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 997ca5d2-eb9a-55b3-9c72-db2223c2f9af
DOI: 10.21203/rs.3.rs-534947/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Deep Learning with Diverse Objectives Improves ARDS PredictionDOI 10.21203/rs.3.rs-534947/v1Read

Development and validation of a dynamic prediction model for unplanned ICU admission and mortality in hospitalized patientsSemantic proximity Read

Deep Neural Network Analysis of Clinical Variables Predicts Escalated Care in COVID-19 PatientsSemantic proximity Read

Predicting Near-term Mortality in Heart Failure: External Validation of Electronic Health Record-Based Deep Learning ModelSemantic proximity Read

Multicenter analysis of COVID-19 hospitalizations and stacking machine learning algorithms for prediction of high-risk patientsSemantic proximity Read

Machine learning for predicting clinical outcomes in emergency department patients with acute respiratory infections: A scoping reviewSemantic proximity Read

Deep Learning Identifies Novel Subphenotypes of Multiple Organ Dysfunction Syndrome in Critical CareSemantic proximity Read

Development and External Validation of a High-Precision Model for Predicting ICU Admission from Emergency Department TriageSemantic proximity Read

Time-Series Deep Learning and Conformal Prediction for Improved Sepsis Diagnosis in Non-ICU Hospitalized PatientsSemantic proximity Read

A Foundation Model for Intensive Care: Unlocking Generalization across Tasks and Domains at ScaleSemantic proximity Read

Evaluating Deep Learning Sepsis Prediction Models in ICUs Under Distribution Shift: A Multi-Centre Retrospective Cohort StudySemantic proximity Read

Predicting Severe COVID-19 Patients Based on Deep Learning: An Application of DeepFM ModelSemantic proximity Read

Unsupervised Cluster-Augmented Mortality Prediction in MIMIC-IV Using Tabular ICU Time-Series Aggregation and Gradient Boosted LearningSemantic proximity Read