Predicting Hospital Readmission Risk for Heart Failure Patients Using Machine Learning Techniques: A Comparative Study of Classification Algorithms-Reference-Cited by-同舟云学术

Predicting Hospital Readmission Risk for Heart Failure Patients Using Machine Learning Techniques: A Comparative Study of Classification Algorithms

Published:2023-08-23 Issue: Volume: Page:
ISSN:
Container-title:2023 Second International Conference on Trends in Electrical, Electronics, and Computer Engineering (TEECCON)
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Author:

Burugadda Venkata Raghuveer¹,Pawar Prashant S.²,Kumar Abhishek³,Bhati Neha⁴

Affiliation:

1. Sr. Solution Architect Western Union Financial Services,Austin,US

2. Krishna Institute of Medical Sciences,Department of Cardiology,Karad,Maharashtra,India

3. Chandigarh University,Department of CSE,Mohali,Punjab,India

4. AVN Innovations,Department of Research & Development,Ajmer,Rajasthan,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10335696/10335697/10335817.pdf?arnumber=10335817

Reference19 articles.

1. Cardiovascular complications of hospitalized patients with COVID-19: A systematic review and meta-analysis;Arora;J Am Heart Assoc.,2021

2. Artificial Intelligence in Precision Cardiovascular Medicine

3. Predicting hospital readmission risk for heart failure patients using machine learning techniques: A systematic review;Amiri;Expert Syst Appl.,2021

4. Design and Development of Consensus Activation Function Enabled Neural Network-Based Smart Healthcare Using BIoT

5. Predicting hospital readmission risk of patients with chronic heart failure using machine learning techniques;Alassaf;J Biomed Inform.,2021

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