Evidence map›Paper›PMID 34003842›Full record

ArticlePloS one2021

A systematic approach to the scale separation problem in the development of multiscale models.

Pinaki Bhattacharya, Qiao Li, Damien Lacroix, Visakan Kadirkamanathan, Marco Viceconti

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Pinaki BhattacharyaDepartment of Mechanical Engineering, University of Sheffield, Sheffield, United Kingdom.ORCID 0000-0003-1109-1174
Qiao LiDepartment of Mechanical Engineering, University of Sheffield, Sheffield, United Kingdom.
Damien LacroixDepartment of Mechanical Engineering, University of Sheffield, Sheffield, United Kingdom.
Visakan KadirkamanathanINSIGNEO Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom.
Marco VicecontiDipartimento di Ingegneria Industriale, Alma Mater Studiorum - University of Bologna, Bologna, Italy.

Funding

Medical Research Council G0601272
6 · The paper itself

Abstract

Throughout engineering there are problems where it is required to predict a quantity based on the measurement of another, but where the two quantities possess characteristic variations over vastly different ranges of time and space. Among the many challenges posed by such 'multiscale' problems, that of defining a 'scale' remains poorly addressed. This fundamental problem has led to much confusion in the field of biomedical engineering in particular. The present study proposes a definition of scale based on measurement limitations of existing instruments, available computational power, and on the ranges of time and space over which quantities of interest vary characteristically. The definition is used to construct a multiscale modelling methodology from start to finish, beginning with a description of the system (portion of reality of interest) and ending with an algorithmic orchestration of mathematical models at different scales within the system. The methodology is illustrated for a specific but well-researched problem. The concept of scale and the multiscale modelling approach introduced are shown to be easily adaptable to other closely related problems. Although out of the scope of this paper, we believe that the proposed methodology can be applied widely throughout engineering.

Indexed as

Biomedical EngineeringComputer SimulationData Interpretation, StatisticalEvaluation Studies as TopicHumansModels, BiologicalModels, TheoreticalTechnology Assessment, Biomedical

Identifiers

PMID34003842
PMCPMC8130972

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Registered trials

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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.