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Prediction of Fluctuations in a Chaotic Cancer Model Using Machine Learning

https://doi.org/10.2139/ssrn.4156477
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15/15 checkable references clean · checked 2026-09-02

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

18 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 15 checked references that resolve
resolves10.1007/978-0-8176-8119-7
A Survey of Models for Tumor-Immune System Dynamics
resolves10.1515/ijnsns-2017-0206
Stability Analysis of a Mathematical Model for Glioma-Immune Interaction under Optimal Therapy
resolves10.1016/j.biosystems.2013.12.001
Model for tumour growth with treatment by continuous and pulsed chemotherapy
resolves10.1016/j.jtbi.2015.01.006
Mathematical model of brain tumour with glia–neuron interactions and chemotherapy treatment
resolves10.1016/j.jtbi.2019.03.002
Mathematical modeling of tumor-immune cell interactions
resolves10.1007/s12064-018-0261-x
Mathematical modeling of cancer–immune system, considering the role of antibodies
resolves10.1016/j.neunet.2012.11.011
Reservoir computing and extreme learning machines for non-linear time-series data analysis
resolves10.1162/NECO_a_00411
Echo State Property Linked to an Input: Exploring a Fundamental Characteristic of Recurrent Neural Networks
resolves10.1103/PhysRevE.91.020801
Reservoir computing with a single time-delay autonomous Boolean node
resolves10.1063/1.5119187
Reconstructing bifurcation diagrams only from time-series data generated by electronic circuits in discrete-time dynamical systems
resolves10.1016/j.jtbi.2013.01.003
What can be learned from a chaotic cancer model?
resolves10.1142/S1793524520500096
Chaotic dynamics of a delayed tumor–immune interaction model
resolves10.1109/TNNLS.2020.3001377
Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series
resolves10.1504/IJAPR.2016.079733
Principal component analysis - a tutorial
resolves10.1109/TNNLS.2016.2630802
Investigating Echo-State Networks Dynamics by Means of Recurrence Analysis
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no DOI — not checkedBidirectional deep-readout echo state networks
no DOI — not checkedref32
no DOI — not checkedref33
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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