Guiying Wang
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Machine learning to develop and validate a model for predicting the risk of lymph node metastasis in colorectal cancer patients
Abstract Background: The presence of lymph node metastasis (LNM) serves as a critical determinant of prognosis in colorectal cancer (CRC), often correlating with markedly unfavorable clinical outcomes. Consequently, this investigation sought to construct and rigorously validate a machine learning (ML) algorithm capable of estimating LNM probability within the CRC population.
An Atomically Dispersed Pd Sub‐Metallene: Intermediate State of Single Atoms and Metal Bonds
Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description adma202504603-sup-0001-SuppMat.docx11.1 MB Supporting Information adma202504603-sup-0002-MovieS1.mpg13.7 MB Supplemental Movie 1 adma202504603-sup-0003-MovieS2.mpg13.7 MB Supplemental Movie 2 adma202504603-sup-0004-MovieS3.mp412.5 MB Supplemental Movie 3 References 1, , Chem. Soc. Rev. 2021, 50, 6700. 2, , Chem. Rev. 2020, 120, 1085. 3, , , , Adv. Mater. 2024, 36, 2210481. 4, , , , , Prog. Mater.
Insights into a Novel and Efficient Microbial Nest System for Treating Pig Farm Wastewater
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