Evidence map›Paper›PMID 34989198›Full record

ArticleJournal of biomedical optics2022

MCX Cloud-a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing.

Qianqian Fang, Shijie Yan

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical optics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
9.5field-weighted citation impact, top 2% of its field
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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

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  12. AI-boosted and motion-corrected, wireless near-infrared sensing system for continuously monitoring laryngeal muscles.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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

2 authors at 1 institution in 1 country.

Qianqian FangNortheastern University, Department of Bioengineering, Boston, Massachusetts, United States.
Shijie YanNortheastern University, Department of Electrical and Computer Engineering, Boston, Massachusetts, United States.
Northeastern University · US

Funding

Next-generation Monte Carlo eXtreme Light Transport Simulation PlatformR01GM114365 · NIGMS · NORTHEASTERN UNIVERSITY · PI FANG, QIANQIAN · 2015 to 2023
$2.9M
NeuroJSON - A Scalable, Searchable and Verifiable Neuroimaging Data PlatformU24NS124027 · NINDS · NORTHEASTERN UNIVERSITY · PI Qianqian Fang · 2021 to 2026
$1.8M
Next-generation optical brain functional imaging platformR01EB026998 · NIBIB · NORTHEASTERN UNIVERSITY · PI FANG, QIANQIAN · 2018 to 2019
$870k
NIBIB NIH HHS R01 EB026998NIGMS NIH HHS R01 GM114365NINDS NIH HHS U24 NS124027
6 · The paper itself

Abstract

significanceDespite the ample progress made toward faster and more accurate Monte Carlo (MC) simulation tools over the past decade, the limited usability and accessibility of these advanced modeling tools remain key barriers to widespread use among the broad user community.

aimAn open-source, high-performance, web-based MC simulator that builds upon modern cloud computing architectures is highly desirable to deliver state-of-the-art MC simulations and hardware acceleration to general users without the need for special hardware installation and optimization. APPROACH: We have developed a configuration-free, in-browser 3D MC simulation platform-Monte Carlo eXtreme (MCX) Cloud-built upon an array of robust and modern technologies, including a Docker Swarm-based cloud-computing backend and a web-based graphical user interface (GUI) that supports in-browser 3D visualization, asynchronous data communication, and automatic data validation via JavaScript Object Notation (JSON) schemas.

resultsThe front-end of the MCX Cloud platform offers an intuitive simulation design, fast 3D data rendering, and convenient simulation sharing. The Docker Swarm container orchestration backend is highly scalable and can support high-demand GPU MC simulations using MCX over a dynamically expandable virtual cluster.

conclusionMCX Cloud makes fast, scalable, and feature-rich MC simulations readily available to all biophotonics researchers without overhead. It is fully open-source and can be freely accessed at http://mcx.space/cloud.

Indexed as

Cloud ComputingSoftwareComputersComputer SimulationMonte Carlo Methodcloud computinglight transportMonte Carlo methodoptical imaging

Identifiers

PMID34989198
PMCPMC8728956
OpenAlexW4205257626

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.