Analysis of relationship between tumor markers and detection of tumors by chemiluminescence immunoassay and artificial neural networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-08855-w.pdf
Reference30 articles.
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3. Busari SA, Huq KMS, Mumtaz S et al (2019) Generalized hybrid beamforming for vehicular connectivity using THz massive MIMO. IEEE Trans Veh Technol 68(9):8372–8383
4. Chen W, Jie WU, Chen Z et al (2012) Chemiluminescent immunoassay and its applications. Chin J Anal Chem 40(1):3–10
5. Chen Y, Liu H, Wang X (2019) Integration of chemiluminescence immunoassay and artificial neural networks for improved cancer screening. Sensors 19(4):856
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1. Group penalized logistic regression differentiates between benign and malignant ovarian tumors;Soft Computing;2023-10-10
2. Correction to: Analysis of relationship between tumor markers and detection of tumors by chemiluminescence immunoassay and artificial neural networks;Soft Computing;2023-08-07
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