Evidence map›Paper›PMID 35028522›Full record

ArticleGeneral psychiatry2021

INCloud: integrated neuroimaging cloud for data collection, management, analysis and clinical translations.

Qingfeng Li, Lijuan Jiang, Kaini Qiao, Yang Hu, Bing Chen, Xiaochen Zhang, Yue Ding, Zhi Yang, Chunbo Li

Abstract read
In one paragraph

Article in General psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

9 authors.

Qingfeng Li *Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Lijuan Jiang *Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Kaini QiaoShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yang HuShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Bing ChenJing Hengyi School of Education, Hangzhou Normal University, Hangzhou, Zhejiang, China.
Xiaochen ZhangShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-1851-0098
Yue DingShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhi YangShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Chunbo LiShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-3387-4439

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeuroimaging techniques provide rich and accurate measures of brain structure and function, and have become one of the most popular methods in mental health and neuroscience research. Rapidly growing neuroimaging research generates massive amounts of data, bringing new challenges in data collection, large-scale data management, efficient computing requirements and data mining and analyses.

aimsTo tackle the challenges and promote the application of neuroimaging technology in clinical practice, we developed an integrated neuroimaging cloud (INCloud). INCloud provides a full-stack solution for the entire process of large-scale neuroimaging data collection, management, analysis and clinical applications.

methodsINCloud consists of data acquisition systems, a data warehouse, automatic multimodal image quality check and processing systems, a brain feature library, a high-performance computing cluster and computer-aided diagnosis systems (CADS) for mental disorders. A unique design of INCloud is the brain feature library that converts the unit of data management from image to image features such as hippocampal volume. Connecting the CADS to the scientific database, INCloud allows the accumulation of scientific data to continuously improve the accuracy of objective diagnosis of mental disorders.

resultsUsers can manage and analyze neuroimaging data on INCloud, without the need to download them to the local device. INCloud users can query, manage, analyze and share image features based on customized criteria. Several examples of 'mega-analyses' based on the brain feature library are shown.

conclusionsCompared with traditional neuroimaging acquisition and analysis workflow, INCloud features safe and convenient data management and sharing, reduced technical requirements for researchers, high-efficiency computing and data mining, and straightforward translations to clinical service. The design and implementation of the system are also applicable to imaging research platforms in other fields.

Indexed as

cloud computingcomputer-aided diagnosis systemcomputing systemdata analysis systemdata sharingneuroimaging

Identifiers

PMID35028522
PMCPMC8705204

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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.