Unveiling Key Predictors for Early Heart Attack Detection using Machine Learning and Explainable AI Technique with LIME-Reference-Cited by-同舟云学术

Unveiling Key Predictors for Early Heart Attack Detection using Machine Learning and Explainable AI Technique with LIME

Published:2023-12-21 Issue: Volume: Page:
ISSN:
Container-title:10th International Conference on Networking, Systems and Security
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Author:

Paudel Prakash¹^ORCID,Karna Satish Kumar¹^ORCID,Saud Ruby¹^ORCID,Regmi Loknath²^ORCID,Thapa Tara Bahadur³^ORCID,Bhandari Mohan⁴^ORCID

Affiliation:

1. Department of IT, Nepal College of Information Technology, Nepal

2. Department of Computer and Electronics, Institute of Engineering, Tribhuvan University, Nepal

3. Department of Engineering and Science, Gandaki College of Engineering and Science, Nepal

4. Department of Science and Technology, Samriddhi College, Nepal

Publisher

ACM

Reference32 articles.

1. A smart healthcare monitoring system for heart disease prediction based on ensemble deep learning and feature fusion

2. Implementation of machine learning model to predict heart failure disease;Alotaibi Fahd Saleh;International Journal of Advanced Computer Science and Applications,2019

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4. Bharath011. 2023. Heart Disease Classification Dataset. https://www.kaggle.com/datasets/bharath011/heart-disease-classification-dataset Accessed : 2023 , august 10. Bharath011. 2023. Heart Disease Classification Dataset. https://www.kaggle.com/datasets/bharath011/heart-disease-classification-dataset Accessed: 2023, august 10.

5. Rohit Bharti , Aditya Khamparia , Mohammad Shabaz , Gaurav Dhiman , Sagar Pande , and Parneet Singh . 2021. Prediction of heart disease using a combination of machine learning and deep learning. Computational intelligence and neuroscience 2021 ( 2021 ). Rohit Bharti, Aditya Khamparia, Mohammad Shabaz, Gaurav Dhiman, Sagar Pande, and Parneet Singh. 2021. Prediction of heart disease using a combination of machine learning and deep learning. Computational intelligence and neuroscience 2021 (2021).