An Improved Concatenation of Deep Learning Models for Predicting and Interpreting Ischemic Stroke

An Improved Concatenation of Deep Learning Models for Predicting and Interpreting Ischemic Stroke

Early detection of stroke warning symptoms can help reduce the severity of ischemic stroke, the leading cause of mortality and disability worldwide. This study aims to develop a model to predict the disease by leveraging machine learning-based models. A model that concatenates a convolutional neural...

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Bibliographic Details
Main Authors: Sapiah Sakri, Shakila Basheer, Zuhaira Muhammad Zain, Nurul Halimatul Asmak Ismail, Dua' Abdellatef Nassar, Ghadah Nasser Aldehim, Mais Ayman Alharaki
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Ischemic stroke prediction
SHAP method
hybrid deep learning model
machine learning
Online Access:https://ieeexplore.ieee.org/document/10494753/

Internet

https://ieeexplore.ieee.org/document/10494753/

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