Evidence map›Paper›PMID 27558834›Full record

ArticleJournal of medical Internet research2016

Datathons and Software to Promote Reproducible Research.

Leo Anthony Celi, Sharukh Lokhandwala, Robert Montgomery, Christopher Moses, Tristan Naumann, Tom Pollard, Daniel Spitz, Robert Stretch

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.6field-weighted citation impact, top 23% 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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Critical Care, Critical Data.Biomedical engineering and computational biology · 2019
    Review
  9. 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

8 authors at 2 institutions in 1 country.

Leo Anthony CeliCritical Data, Massachusetts Institute of Technology, Cambridge, MA, United States.ORCID 0000-0001-6712-6626
Sharukh LokhandwalaORCID 0000-0002-2573-388X
Robert MontgomeryORCID 0000-0001-9914-6082
Christopher MosesORCID 0000-0003-4172-4446
Beth Israel Deaconess Medical Center · USMassachusetts Institute of Technology · US

Funding

Integrating Data, Models, and Reasoning in Critical CareR01EB001659 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI MARK, ROGER GREENWOOD · 2003 to 2012
$9.8M
Research Resource for Complex Physiologic SignalsR01GM104987 · NIGMS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI GOLDBERGER, ARY LOUIS, MARK, ROGER GREENWOOD · 2012 to 2019
$5.8M
Critical Care Informatics: Ethical considerations around the use and sharing of health-related dataR01EB017205 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI CELI, LEO ANTHONY G, MARK, ROGER GREENWOOD · 2014 to 2021
$3.8M
NIBIB NIH HHS R01 EB001659NIBIB NIH HHS R01 EB017205NIGMS NIH HHS R01 GM104987
6 · The paper itself

Abstract

backgroundDatathons facilitate collaboration between clinicians, statisticians, and data scientists in order to answer important clinical questions. Previous datathons have resulted in numerous publications of interest to the critical care community and serve as a viable model for interdisciplinary collaboration.

objectiveWe report on an open-source software called Chatto that was created by members of our group, in the context of the second international Critical Care Datathon, held in September 2015.

methodsDatathon participants formed teams to discuss potential research questions and the methods required to address them. They were provided with the Chatto suite of tools to facilitate their teamwork. Each multidisciplinary team spent the next 2 days with clinicians working alongside data scientists to write code, extract and analyze data, and reformulate their queries in real time as needed. All projects were then presented on the last day of the datathon to a panel of judges that consisted of clinicians and scientists.

resultsUse of Chatto was particularly effective in the datathon setting, enabling teams to reduce the time spent configuring their research environments to just a few minutes-a process that would normally take hours to days. Chatto continued to serve as a useful research tool after the conclusion of the datathon.

conclusionsThis suite of tools fulfills two purposes: (1) facilitation of interdisciplinary teamwork through archiving and version control of datasets, analytical code, and team discussions, and (2) advancement of research reproducibility by functioning postpublication as an online environment in which independent investigators can rerun or modify analyses with relative ease. With the introduction of Chatto, we hope to solve a variety of challenges presented by collaborative data mining projects while improving research reproducibility.

Indexed as

InternetSoftwareBiomedical ResearchData MiningHumansMedical InformaticsReproducibility of Resultsbig datadatabaseInternetmedical informaticsreproducibility of findings

Identifiers

PMID27558834
PMCPMC5014984
OpenAlexW2510282201

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.