A Survey on Image-Based Cardiac Diagnosis Prediction Using Machine Learning and Deep Learning Techniques
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Cardiac imaging is crucial in the diagnosis of cardiovascular disease. Cardiovascular disease is the umbrella term for the majority of heart ailments. The majority of the causes of mortality are associated with cardiovascular illness. The authors provide a technique for the diagnosis of cardiac disease. The main aim of this study is to determine the most effective technique for predicting cardiovascular disease, specifically focusing on the use of signs of heart disease and Electrocardiogram images. This will be achieved by leveraging the latest advancements in Deep Learning and Machine Learning methods. The authors conduct a comprehensive examination of various Machine Learning and Deep Learning Techniques. These techniques were evaluated in the context of predicting cardiovascular disease evaluating Image. The analysis shows that the Convolutional Neural Network methods are much more effective than the alternatives. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Açıklama
2nd International Conference on Computing, IoT and Data Analytics, ICCIDA 2023 -- 20 July 2023 through 21 July 2023 -- -- 308639
Anahtar Kelimeler
Cardiac İmaging, Cardiovascular Disease, Cnn, Deep Learning, Ecg İmages, Machine Learning
Kaynak
Studies in Computational Intelligence
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
1145 SCI
