A Machine Learning Based Predictive Model to Diagnose Heart Failure Patients using Imbalanced Classification Problem-Reference-Cited by-同舟云学术

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A Machine Learning Based Predictive Model to Diagnose Heart Failure Patients using Imbalanced Classification Problem

Published:2023-02-20 Issue: Volume: Page:
ISSN:
Container-title:2023 4th International Conference on Advancements in Computational Sciences (ICACS)
language:
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Author:

Mudassar Muhammad¹,Afzal Mehtab²,Muhammad Tufail³

Affiliation:

1. Univeristy of Lahore,Department of Software Engineering,Lahore,Pakistan

2. University of Lahore,Department of Computer Science and Information Technology,Lahore,Pakistan

3. Air Univeristy Islamabad, Aerospace and Aviation Campus,Department of Computer Science,Kamra,Pakistan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10089613/10089626/10089759.pdf?arnumber=10089759

Reference27 articles.

1. A Comparison of Oversampling Methods for Constructing a Prognostic Model in the Patient with Heart Failure

2. Gender based survival prediction models for heart failure patients: A case study in Pakistan

3. Machine Learning Techniques for Heart Failure Prediction: An Exclusively Feature Selective Approach

4. Development of an Explainable Prediction Model of Heart Failure Survival by Using Ensemble Trees

5. Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone

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