Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes.

PloS one - 1 Jan 2024

Christensen Mathias Aagaard, Sigurdsson Arnór, Bonde Alexander, Rasmussen Simon, Ostrowski Sisse R, Nielsen Mads, Sillesen Martin

Abstract excerpt

INTRODUCTION: Postoperative complications affect up to 15% of surgical patients constituting a major part of the overall disease burden in a modern healthcare system. While several surgical risk calculators have been developed, none have so far been shown to decrease the associated mortality and morbidity. Combining deep neural networks and genomics with the already established clinical predictors may hold...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Atrial Fibrillation
Share to Deep Learning

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Neural Networks, Computer

Share to Pneumonia

Share to Postoperative Complications

Share to Risk Assessment

Share to ROC Curve

Share to Venous Thromboembolism

Source

Open in PubMed Open full text

Identifiers

PMID: 39008506
DOI: 10.1371/journal.pone.0294368
PMCID: PMC11249253

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes.PMID 39008506Read ↗

An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomesSemantic proximity Read ↗

Genetic risk factors for postoperative complications after major surgery and shared genetic aetiology with non-postoperative phenotypesSemantic proximity Read ↗

Genetic and clinical risk prediction model for postoperative atrial fibrillation.Semantic proximity Read ↗

Predictive Accuracy of a Polygenic Risk Score for Postoperative Atrial Fibrillation After Cardiac Surgery.Semantic proximity Read ↗

Novel Preoperative Risk Stratification Using Digital Phenotyping Applying a Scalable Machine-Learning Approach.Semantic proximity Read ↗

Neural network-based integration of polygenic and clinical information: development and validation of a prediction model for 10-year risk of major adverse cardiac events in the UK Biobank cohort.Semantic proximity Read ↗

Genetic Susceptibility to Incisional Hernia Evaluation of Hernia Polygenic Risk ScoresSemantic proximity Read ↗

Prediction of atrial fibrillation and stroke using machine learning models in UK BiobankSemantic proximity Read ↗

Polygenic risk scores for prediction of cancer-associated venous thromboembolism in the UK Biobank cohort studySemantic proximity Read ↗

Integrating Genome-Wide Polygenic Risk Scores With Nongenetic Models to Predict Surgical Site Infection After Total Knee Arthroplasty Using United Kingdom Biobank Data.Semantic proximity Read ↗

Genomics: risk and outcomes in cardiac surgery.Semantic proximity Read ↗

Prediction of primary venous thromboembolism based on clinical and genetic factors within the U.K. Biobank.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.