Readmission prediction using deep learning on electronic health records-Reference-Cited by-同舟云学术

Readmission prediction using deep learning on electronic health records

Published:2019-09 Issue: Volume:97 Page:103256
ISSN:1532-0464
Container-title:Journal of Biomedical Informatics
language:en
Short-container-title:Journal of Biomedical Informatics

Author:

Ashfaq Awais^ORCID,Sant’Anna Anita,Lingman Markus,Nowaczyk Sławomir

Funder

European Regional Development Fund

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference59 articles.

1. Trends in 30-day readmission rates for patients hospitalized with heart failure: findings from the get with the guidelines-heart failure registry;Bergethon;Circul.: Heart Fail.,2016

2. Why do patients keep coming back? Results of a readmitted patient survey;Felix;Soc. Work Health Care,2015

3. Hospital readmissions reduction program;McIlvennan;Circulation,2015

4. Reducing hospital readmission rates: current strategies and future directions;Kripalani;Annu. Rev. Med.,2014

5. Utility of models to predict 28-day or 30-day unplanned hospital readmissions: an updated systematic review;Zhou;BMJ Open,2016

Cited by 123 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Graph and text multi-modal representation learning with momentum distillation on Electronic Health Records;Knowledge-Based Systems;2024-10

2. Reconfiguration of uncertainty: Introducing AI for prediction of mortality at the emergency department;Social Science & Medicine;2024-10

3. Self-Supervised Forecasting in Electronic Health Records With Attention-Free Models;IEEE Transactions on Artificial Intelligence;2024-08

4. SHAP based predictive modeling for 1 year all-cause readmission risk in elderly heart failure patients: feature selection and model interpretation;Scientific Reports;2024-07-31

5. Time series forecasting of weight for diuretic dose adjustment using bidirectional long short-term memory;Scientific Reports;2024-07-31