A "datathon" model to support cross-disciplinary collaboration. - Wikidata - awgldk - TriplyDB

A "datathon" model to support cross-disciplinary collaboration.

A "datathon" model to support cross-disciplinary collaboration.

http://www.wikidata.org/entity/Q30277020

about

Datathons and Software to Promote Reproducible Research MIMIC-III, a freely accessible critical care database Bridging the Health Data Divide.Ethics and Epistemology in Big Data Research.Healthcare Hackathons Provide Educational and Innovation Opportunities: A Case Study and Best Practice Recommendations Methods for enhancing the reproducibility of biomedical research findings using electronic health records.Promoting Secondary Analysis of Electronic Medical Records in China: Summary of the PLAGH-MIT Critical Data Conference and Health Datathon.Enabling Machine Learning in Critical Care Translating Science Into Business Innovation: The Case of Open Food and Nutrition Data Hackathons

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P2860

A "datathon" model to support cross-disciplinary collaboration.

http://www.wikidata.org/entity/Q30277020

description

2016 nî lūn-bûn

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2016 թուականի Ապրիլին հրատարակուած գիտական յօդուած

@hyw

2016 թվականի ապրիլին հրատարակված գիտական հոդված

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2016年の論文

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2016年論文

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2016年論文

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2016年論文

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2016年論文

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2016年論文

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2016年论文

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name

A "datathon" model to support cross-disciplinary collaboration.

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A "datathon" model to support cross-disciplinary collaboration.

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A "datathon" model to support cross-disciplinary collaboration.

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A "datathon" model to support cross-disciplinary collaboration.

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A "datathon" model to support cross-disciplinary collaboration.

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A "datathon" model to support cross-disciplinary collaboration.

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Science Translational Medicine

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A "datathon" model to support cross-disciplinary collaboration.

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Jerôme Aboab

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Justin D Salciccioli

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Kenneth E Paik

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Louis Mayaud

http://www.w3.org/2001/XMLSchema#string

Mengling Feng

http://www.w3.org/2001/XMLSchema#string

Mohammad Ghassemi

http://www.w3.org/2001/XMLSchema#string

Ned McCague

http://www.w3.org/2001/XMLSchema#string

Tom J Pollard

http://www.w3.org/2001/XMLSchema#string

P2860

Best practices for scientific computing

How to make more published research true

IPython: A System for Interactive Scientific Computing

Biomedical research: increasing value, reducing waste

The case for open computer programs

Acquisition, Analysis, and Sharing of Data in 2015 and Beyond: A Survey of the Landscape: A Conference Report From the American Heart Association Data Summit 2015

Increasing value and reducing waste: addressing inaccessible research

Beyond open big data: addressing unreliable research.

The association between the neutrophil-to-lymphocyte ratio and mortality in critical illness: an observational cohort study.

Increasing value and reducing waste in research design, conduct, and analysis

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333

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8

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Matthieu Resche-Rigon

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Tristan Naumann

Dominic C Marshall

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2016-04-01T00:00:00Z

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reproducibility

transdisciplinarity

medical research

data collaboration

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