scholarly journals On Reproducible AI: Towards Reproducible Research, Open Science, and Digital Scholarship in AI Publications

AI Magazine ◽  
2018 ◽  
Vol 39 (3) ◽  
pp. 56-68 ◽  
Author(s):  
Odd Erik Gundersen ◽  
Yolanda Gil ◽  
David W. Aha
Keyword(s):  
Artificial Intelligence ◽  
Best Practices ◽  
Open Science ◽  
Reproducible Research ◽  
Artificial Intelligence Research ◽  
Digital Scholarship ◽  
Reproducible Method ◽  
Provided Examples

Background: Science is experiencing a reproducibility crisis. Artificial intelligence research is not an exception. Objective: To give practical and pragmatic recommendations for how to document AI research so that the results are reproducible. Method: Our analysis of the literature shows that AI publications fall short of providing enough documentation to facilitate reproducibility. Our suggested best practices are based on a framework for reproducibility and recommendations given for other disciplines. Results: We have made an author checklist based on our investigation and provided examples for how every item in the checklist can be documented. Conclusion: We encourage reviewers to use the suggested best practices and author checklist when reviewing submissions for AAAI publications and future AAAI conferences.

scholarly journals Mapping the landscape of Artificial Intelligence applications against COVID-19

2020 ◽  
Vol 69 ◽  
pp. 807-845 ◽  
Author(s):  
Joseph Bullock ◽  
Alexandra Luccioni ◽  
Katherine Hoffman Pham ◽  
Cynthia Sin Nga Lam ◽  
Miguel Luengo-Oroz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Open Science ◽  
Data Sources ◽  
World Health ◽  
Artificial Intelligence Research ◽  
Non Invasive ◽  
Multiple Data ◽  
The World ◽  
Health Organization

COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, which has reported over 18 million confirmed cases as of August 5, 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID19 crisis. We have identified applications that address challenges posed by COVID-19 at different scales, including: molecular, by identifying new or existing drugs for treatment; clinical, by supporting diagnosis and evaluating prognosis based on medical imaging and non-invasive measures; and societal, by tracking both the epidemic and the accompanying infodemic using multiple data sources. We also review datasets, tools, and resources needed to facilitate Artificial Intelligence research, and discuss strategic considerations related to the operational implementation of multidisciplinary partnerships and open science. We highlight the need for international cooperation to maximize the potential of AI in this and future pandemics.

scholarly journals How To Publish: Preparing Manuscripts for Clarity, Transparency, Scholarly Integrity, and Success

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 858-858
Author(s):  
Suzanne Meeks
Keyword(s):  
Best Practices ◽  
Round Table ◽  
Open Science ◽  
High Impact ◽  
Publication Ethics ◽  
Scholarly Work ◽  
Scholarly Writing ◽  
Annual Symposium ◽  
The Right

Abstract The GSA publications team sponsors this annual symposium to assist prospective authors to successfully publish their gerontological scholarship in GSA’s high impact and influential journals. The first part of the session will include five brief presentations from the Editors-in-chief of Journals of Gerontology-Series B, Social and Psychological Sciences, The Gerontologist, and Innovation in Aging, plus one of GSA’s managing editors. We will integrate practical tips with principles of publication ethics and scholarly integrity. The topics will be as follows: (1) preparing your manuscript, including how to choose the right journal; (2) strong and ethical scholarly writing for multidisciplinary audiences; (3) transparency, documentation, and Open Science; (4) successfully responding to reviews; and (5) working with Scholar One. Following these presentations, we will hold round table discussions with editors from the GSA journals portfolio. At these roundtables, editors will answer questions related to the podium presentations and other questions specific to each journal. Intended audiences include emerging and international scholars, and authors interested in learning more about best practices and tips for getting their scholarly work published.

scholarly journals WORCS: A workflow for open reproducible code in science

Data Science ◽  
2021 ◽  
pp. 1-21
Author(s):  
Caspar J. Van Lissa ◽  
Andreas M. Brandmaier ◽  
Loek Brinkman ◽  
Anna-Lena Lamprecht ◽  
Aaron Peikert ◽  
...  
Keyword(s):  
Best Practices ◽  
Source Code ◽  
R Package ◽  
Open Science ◽  
Research Projects ◽  
Tabular Data ◽  
Step Procedure ◽  
Starting Point ◽  
Conducting Research ◽  
And Training

Adopting open science principles can be challenging, requiring conceptual education and training in the use of new tools. This paper introduces the Workflow for Open Reproducible Code in Science (WORCS): A step-by-step procedure that researchers can follow to make a research project open and reproducible. This workflow intends to lower the threshold for adoption of open science principles. It is based on established best practices, and can be used either in parallel to, or in absence of, top-down requirements by journals, institutions, and funding bodies. To facilitate widespread adoption, the WORCS principles have been implemented in the R package worcs, which offers an RStudio project template and utility functions for specific workflow steps. This paper introduces the conceptual workflow, discusses how it meets different standards for open science, and addresses the functionality provided by the R implementation, worcs. This paper is primarily targeted towards scholars conducting research projects in R, conducting research that involves academic prose, analysis code, and tabular data. However, the workflow is flexible enough to accommodate other scenarios, and offers a starting point for customized solutions. The source code for the R package and manuscript, and a list of examplesof WORCS projects, are available at https://github.com/cjvanlissa/worcs.

scholarly journals RECOMIA—a cloud-based platform for artificial intelligence research in nuclear medicine and radiology

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Elin Trägårdh ◽  
Pablo Borrelli ◽  
Reza Kaboteh ◽  
Tony Gillberg ◽  
Johannes Ulén ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Nuclear Medicine ◽  
Artificial Intelligence Research
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