Forecasting the Survival and Mortality of Patients by Machine Learning Trained on Heart Failure Clinical Imbalanced Data-Reference-Cited by-同舟云学术

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Forecasting the Survival and Mortality of Patients by Machine Learning Trained on Heart Failure Clinical Imbalanced Data

Published:2024-03-14 Issue: Volume: Page:1-6
ISSN:
Container-title:2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)
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Author:

Rawat Satyendra Singh¹,Mishra Amit Kumar²,Motwani Deepak³

Affiliation:

1. Swami Rama Himalayan University,Department of Computer Science and Engineering,Dehradun,India

2. Amity University,Department of Computer Science and Engineering,Gwalior,India

3. Amity University,Department of Computer Science & Engineering,Gwalior,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10502389/10502407/10502741.pdf?arnumber=10502741

Reference39 articles.

1. Machine Learning Framework for the Detection of Mental Stress at Multiple Levels

2. Stress Analysis Based on Simultaneous Heart Rate Variability and EEG Monitoring

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

4. A Computationally Efficient Approach to Segmentation of the Aorta and Coronary Arteries Using Deep Learning

5. An Imbalanced-Data Processing Algorithm for the Prediction of Heart Attack in Stroke Patients

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