Evidence map›Paper›PMID 36276480›Full record

ArticleAIP conference proceedings2022

A Fokker-Planck Framework for Parameter Estimation and Sensitivity Analysis in Colon Cancer.

S Roy, S Pal, A Manoj, S Kakarla, J V Padilla, M Alajmi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in AIP conference proceedings, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

S RoyDepartment of Mathematics, The University of Texas at Arlington, Arlington, TX 76019-0408, USA.
S PalDepartment of Mathematics, The University of Texas at Arlington, Arlington, TX 76019-0408, USA.
A ManojDepartment of Physics, The University of Texas at Arlington, Arlington, TX 76019-0408, USA.
S KakarlaDepartment of Computer Science, The University of Texas at Arlington, Arlington, TX 76019-0408, USA.
J V PadillaDepartment of Mathematics, The University of Texas at Arlington, Arlington, TX 76019-0408, USA.
M AlajmiDepartment of Mathematics, The University of Texas at Arlington, Arlington, TX 76019-0408, USA.

Funding

Data-driven QSP software for personalized colon cancer treatmentR21CA242933 · NCI · UNIVERSITY OF MASSACHUSETTS AMHERST · PI PAL, SUVRA, ROY, SOUVIK · 2019 to 2020
$547k
NCI NIH HHS R21 CA242933
6 · The paper itself

Abstract

A new stochastic framework for parameter estimation and uncertainty quantification in colon cancer-induced immune response is presented. The dynamics of colon cancer is given by a stochastic process that captures the inherent randomness in the system. The stochastic framework is based on the Fokker-Planck equation that represents the evolution of the probability density function corresponding to the stochastic process. An optimization problem is formulated that takes input individual patient data with randomness present, and is solved to obtain the unknown parameters corresponding to the individual tumor characteristics. Furthermore, sensitivity analysis of the optimal parameter set is performed to determine the parameters that need to be controlled, thus, providing information of the type of drugs that can be used for treatment.

Identifiers

PMID36276480
PMCPMC9583768

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.