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ZENODO
Software . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
ZENODO
Software . 2025
License: CC BY
Data sources: Datacite
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Code for the paper "cytoGPNet: Enhancing Clinical Outcome Prediction Accuracy Using Longitudinal Cytometry Data in Small Cohort Studies"

Authors: Zhang, Jingxuan; Lin, Lin;

Code for the paper "cytoGPNet: Enhancing Clinical Outcome Prediction Accuracy Using Longitudinal Cytometry Data in Small Cohort Studies"

Abstract

Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA provided financial support for TOP1501 study. The opinions expressed in this paper are those of the authors and do not necessarily represent those of Merck Sharp & Dohme LLC. This research was also supported by the Duke University Center for AIDS Research (CFAR), an NIH funded program (5P30 AI064518) and NIH P01 (2 P01 AI129859). The authors gratefully recognize the contributions of Jennifer Enzor and Prekshaben Patel, who generated all of the original TOP1501 flow cytometry data in the Duke Immune Profiling Core (DIPC), a designated Shared Resource of the NIH-sponsored Duke Cancer Institute (5P30-CA014236-50).

The software package provides an implementation of cytoGPNet, as described in the paper "cytoGPNet: Enhancing Clinical Outcome Prediction Accuracy Using Longitudinal Cytometry Data in Small Cohort Studies". Release is on Github here.

Keywords

Deep Learning, Flow Cytometry

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Related to Research communities
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