Prediction of Cardiovascular Disease Through Cutting-Edge Deep Learning Technologies: An Empirical Study Based on TENSORFLOW, PYTORCH and KERAS

Author:

Ashraf Mudasir,Ahmad Syed Mudasir,Ganai Nazir Ahmad,Shah Riaz Ahmad,Zaman Majid,Khan Sameer Ahmad,Shah Aftab Aalam

Publisher

Springer Singapore

Cited by 24 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. Enhancing Road Safety in Diminished Vision Conditions: A Deep Learning Approach Using Faster MobileNet for Real-time Object Detection;2023 4th International Conference on Intelligent Technologies (CONIT);2024-06-21

2. Prediction of Cardiovascular Disease Risk in the General Population: A GSA-ELM Approach;2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC);2024-05-02

3. Brain Stroke Detection Through Advanced Machine Learning and Enhanced Algorithms;2024 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI);2024-04-17

4. Machine intelligence based early prediction methods for Cardiovascular Diseases (CVDs);Journal of Electrical Systems;2024-03-31

5. Heart failure survival prediction using novel transfer learning based probabilistic features;PeerJ Computer Science;2024-03-12

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