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      Application of CT Imaging in Differential Diagnosis and Nursing of Endocrine Tumors

      research-article
      1 , 2 , 1 ,
      Contrast Media & Molecular Imaging
      Hindawi

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          Abstract

          In order to investigate the value of preoperative X-ray computed tomography (CT) in predicting the pathological grade of pancreatic neuroendocrine tumors. This paper retrospectively analyzed the CT image examination of pancreatic neuroendocrine tumors, the image characteristics of G-NEC detected by CT image, and the detection of GST by spiral CT. In order to clearly diagnose and evaluate the size and scope of the focus, whether there is adjacent tissue invasion, metastasis, and treatment effect, CT, MR, PET-CT, nuclide specific imaging, and other imaging methods are widely used in the medical treatment of pNEN patients. These imaging methods have the advantages of noninvasive, rapid imaging, objective image medium, and strong repeatability. If the pathological grade of pNEN patients can be obtained by imaging examination before operation, it will be of great benefit to the formulation of treatment strategies and the prediction of clinical outcomes. Combining CT image performance with imaging omics characteristics to establish a prediction model that can develop a better auxiliary decision-making tool for clinical practice. Different pathological grades prompt clinicians to provide personalized and accurate medical treatment for patients, and reduce excessive medical treatment or wrong judgment caused by unclear preoperative diagnostic information.

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          Progress of zinc oxide‐based nanocomposites in the textile industry

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            Research on the Natural Language Recognition Method Based on Cluster Analysis Using Neural Network

            Withthe technological advent, the clustering phenomenon is recently being used in various domains and in natural language recognition. This article contributes to the clustering phenomenon of natural language and fulfills the requirements for the dynamic update of the knowledge system. This article proposes a method of dynamic knowledge extraction based on sentence clustering recognition using a neural network-based framework. The conversion process from natural language papers to object-oriented knowledge system is studied considering the related problems of sentence vectorization. This article studies the attributes of sentence vectorization using various basic definitions, judgment theorem, and postprocessing elements. The sentence clustering recognition method of the network uses the concept of prereliability as a measure of the credibility of sentence recognition results. An ART2 neural network simulation program is written using MATLAB, and the effect of the neural network on sentence recognition is utilized for the corresponding analysis. A postreliability evaluation indexing is done for the credibility of the model construction, and the implementation steps for the conjunctive rule sentence pattern are specifically introduced. A new method of structural modeling is utilized to generate the structured derivation relationship, thus completing the natural language knowledge extraction process of the object-oriented knowledge system. An application example with mechanical CAD is used in this work to demonstrate the specific implementation of the example, which confirms the effectiveness of the proposed method.
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              Power station flue gas desulfurization system based on automatic online monitoring platform

              X Liu, C Ma, C Yang (2015)
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                Author and article information

                Contributors
                Journal
                Contrast Media Mol Imaging
                Contrast Media Mol Imaging
                CMMI
                Contrast Media & Molecular Imaging
                Hindawi
                1555-4309
                1555-4317
                2022
                8 August 2022
                : 2022
                : 4071081
                Affiliations
                1Department of Endocrinology, The Second Hospital of Jilin University, Changchun, Jinlin 130000, China
                2Department of Oncology and Hematology, The Second Hospital of Jilin University, Changchun 130000, China
                Author notes

                Academic Editor: Sorayouth Chumnanvej

                Author information
                https://orcid.org/0000-0003-4488-7339
                https://orcid.org/0000-0002-6463-5801
                https://orcid.org/0000-0002-3629-1853
                Article
                10.1155/2022/4071081
                9377953
                36043145
                1c68870b-6d38-430f-bc9a-39fbbf68ff37
                Copyright © 2022 Xue Jiang et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 10 June 2022
                : 13 July 2022
                : 21 July 2022
                Categories
                Research Article

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