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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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Claim

Gastric Neuroendocrine Neoplasms based SEER data and external institutional hospital data

Research datakeyboard_double_arrow_right Dataset 04 Feb 2023Publisher:Zenodo
Authors: Lu Liu;

doi: 10.5281/zenodo.7604314 , 10.5281/zenodo.7604315

Gastric Neuroendocrine Neoplasms based SEER data and external institutional hospital data

Abstract

The data including gastric neuroendocrine neoplasms based SEER data and external institutional hospital (First affiliated hospital of Soochow University) data aims to predict the predict the risk of lymph node metastasis among the gastric NENs patients based on the machine learning algorithms. Along with the paper titled Application of Machine Learning Algorithms to Predict Lymph Node Metastasis in Gastric Neuroendocrine Neoplasms, uploaded by author Lu Liu.

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Keywords

SEER, machining learning

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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