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Shujan Shak on Muck Rack

Shujan Shak

As seen in: Nature
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Articles

Cardiovascular disease prediction using variational recurrent autoencoders with uncertainty estimation

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By Ashim Das, Shujan Shak, Nabila Rahman, Fuad Mahmud, Hashibul Shoaib, Jakir Hossen
| Nature Verified
Abstract Cardiovascular diseases (CVDs) remain a leading cause of mortality worldwide, motivating reproducible benchmark studies on accurate classification methods with calibrated probability estimates. In this paper, we propose a deep learning framework based on a Variational Recurrent Autoencoder (VRAE) with uncertainty estimation for CVD classification from static tabular clinical records represented as synthetic noise-augmented pseudo-sequences.
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Cardiovascular disease prediction using variational recurrent autoencoders with uncertainty estimation

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By Ashim Das, Nabila Rahman, Fuad Mahmud, Hashibul Shoaib, Jakir Hossen, Shujan Shak
| Nature Verified
Abstract Cardiovascular diseases (CVDs) remain a leading cause of mortality worldwide, motivating reproducible benchmark studies on accurate classification methods with calibrated probability estimates. In this paper, we propose a deep learning framework based on a Variational Recurrent Autoencoder (VRAE) with uncertainty estimation for CVD classification from static tabular clinical records represented as synthetic noise-augmented pseudo-sequences.
Open in Who Shared Issue with article?
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