2021
DOI: 10.18280/ts.380425
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An Efficient Image Based Feature Extraction and Feature Selection Model for Medical Data Clustering Using Deep Neural Networks

Abstract: The multi-modal health information representing the learning material was examined and multiple learning models were suggested for disease risk assessments, with the aim of mining information from the medical data and developing intelligent applications issues. A medical textual learning model based on a convolution neural network is proposed for the aspect of medical textual functional education. In the framework for risk evaluation, the convolution neural network information retrieval methodology is applied.… Show more

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“…(3) Using different data sets, the performance of this model is tested under different indicators to verify the efficiency of this model. e former mainly reflects the statistical information of the image, while the latter describes the image as a whole based on local structure, texture, and other details [8,9]. Aiming at the deficiency of the original similarity measurement model, the acquisition of the image feature matrix is optimized to ensure the effectiveness of acquiring image feature information.…”
Section: Introductionmentioning
confidence: 99%
“…(3) Using different data sets, the performance of this model is tested under different indicators to verify the efficiency of this model. e former mainly reflects the statistical information of the image, while the latter describes the image as a whole based on local structure, texture, and other details [8,9]. Aiming at the deficiency of the original similarity measurement model, the acquisition of the image feature matrix is optimized to ensure the effectiveness of acquiring image feature information.…”
Section: Introductionmentioning
confidence: 99%