一种用于脑电图检测癫痫患者的深度聚合集合学习模型

2022 IEEE 4th PhD Colloquium on Emerging Domain Innovation and Technology for Society (PhD EDITS) Pub Date : 2022-11-04 DOI:10.1109/PhDEDITS56681.2022.9955308

Sricheta Parui, Uttam Ghosh, Puspita Chatterjee, Deborsi Basu

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引用次数: 1

摘要

在这项研究中，我们开发了一个深度聚合组装学习(DAAL)模型来诊断癫痫，该模型使用两步学习，并利用0级分类器模型的输出预测生成最终预测。在0级CNN中，首先使用RNN和ANN模型，然后使用一种预测算法来预测来自每个模型的每个概率向量的最终输出。

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DAAL: A Deep Aggregated Assemble Learning Model for detecting Epileptic patients from EEG

In this study, we developed a Deep Aggregated Assemble Learning(DAAL) model to diagnose Epilepsy that uses two-step learning and generates the final prediction utilizing the output predictions of the level 0 classifier model. In level 0 CNN, RNN and ANN model has been used, and then a prediction algorithm has been used which predicts the final output from each of the probability vector coming from each model.

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2022 IEEE 4th PhD Colloquium on Emerging Domain Innovation and Technology for Society (PhD EDITS)

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