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<div><p>In health care, an accurate diagnosis with the help of a data-driven forecasting framework takes the risk factors associated with heart disease. However, building such an effective model using deep learning (DL) methods requires high-quality data, i.e., data free of outliers or a...

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Main Author:	Ritika Ritika (10667302) (author)
Other Authors:	Rajender Singh Chhillar (22453795) (author), Sandeep Dalal (22453798) (author), Surjeet Dalal (4906894) (author), Iyyappan Moorthi (22453801) (author), Mitiku Dubale (12506099) (author), Arshad Hashmi (13835488) (author)
Published:	2025
Subjects:	Cancer Science Policy Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified risk factors associated proposed methodology consists nutrition recommendations based methods requires high current paper proposes proposed model attain controlling heart diseases feature extraction methods net dl model feature extraction net model heart disease xlink "> treatment individualization thus improving significantly better prevailing models phase three phase four phase five pearson correlation new approach integrates cnn inception net health care hamming loss first phase detected disease angle detectnet accurate diagnosis
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