Semi-supervised learning: Assisted cardiovascular disease forecasting using self-learning approaches

• Main Authors: Tusher, Ekramul Haque, Mohd Arfian, Ismail, Khan, Ferose, Anis Farihan, Mat Raffei, Md Akbar, Jalal Uddin
• Format: Article
• Language: English; English
• Published: Penerbit Akademia Baru 2024
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/39151/1/Semi-supervised%20learning_%20Assisted%20cardiovascular%20disease%20forecasting.pdf; http://umpir.ump.edu.my/id/eprint/39151/7/Semi-Supervised%20Learning-%20Assisted%20Cardiovascular%20Disease.pdf; http://umpir.ump.edu.my/id/eprint/39151/; https://doi.org/10.37934/araset.56.1.136150; https://doi.org/10.37934/araset.56.1.136150

Cardiovascular diseases (CVDs) are characteristics that affect both the heart and the blood vessels. This disease is the main factor contributing to the greatest number of deaths globally. In the present global context, it is very difficult to detect cardiovascular diseases by early-stage symptoms....