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Cognitive Computation - Call for Papers: Data-Driven Artificial Intelligence approaches to Combat COVID-19

SCOPE AND MOTIVATION

COVID-19, the infectious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus, has been recognised as a pandemic by the World Health Organisation. As of 6th May 2020, there have been over 3.8 million confirmed cases worldwide, with over 2,65K deaths and another over 48K critical cases. Almost every country has been affected significantly, and many have been in a state of lockdown to slow the spread of the infection. The scientific community has been working tirelessly to combat the disease and its adverse effects. Global research efforts are being made in a range of priority COVID-19 areas, including:  

  • Reduction of disease transmission.
  • Application of deep learning for COVID-19 diagnosis and treatment.
  • Identification of infection dynamics; pandemic hotspots and a focused population for screening.
  • Supporting diagnosis, treatment, and the recovery process.
  • Enabling appropriate drug and vaccine development processes.

This timely special issue invites research contributions (both original research and comprehensive survey articles) from all related areas, with a focus on data-driven artificial intelligence (AI) approaches and their applications in combatting COVID-19.

TOPICS

The topics of interest include, but are not limited to:

  • AI methods in COVID-19 related data collection, curation, and visualisation.
  • Application of deep learning for COVID-19 diagnosis and treatment.
  • Data-driven AI identification / tracking of COVID-19 infection transmission and dynamics.
  • Data-driven AI methodologies for future pandemic prediction/prevention.
  • Data-driven AI prediction and awareness measures - regional and global cases.
  • Intelligent and/or data-driven approaches for effective delivery of treatment.
  • Intelligent and/or data-driven approaches for monitoring COVID-19 patients at home.
  • Intelligent and/or data-driven methods to detect COVID-19.
  • Intelligent bioinformatics approaches towards drug design for COVID-19.
  • Intelligent health informatics for tackling COVID-19.
  • Intelligent hospital management for healthcare professionals during COVID-19.

DEADLINES

Submissions Deadline

extended to 31 December 2020

First notification of acceptance

28 February 2021

Submission of revised papers

31 March 2021

Final notification to authors

30 April 2021

Submission of final/camera-ready papers

July 2021

Publication of special issue (provisional)*

Dec 2020/Jan 2021

  *All accepted papers will appear immediately in the journal’s online topical collection


ORGANIZERS/GUEST EDITORS

Mufti Mahmud

(co-ordinator)

Nottingham Trent University, UK

muftimahmud@gmail.com (this opens in a new tab)

mufti.mahmud@ntu.ac.uk

M Shamim Kaiser

Jahangirnagar University, Bangladesh

mskaiser@juniv.edu (this opens in a new tab)  

Nilanjan Dey

Techno India College of Technology, India

nilanjan.dey@tict.edu.in (this opens in a new tab)

Newton Howard

University of Oxford, UK; MIT, USA

nhmit@mit.edu (this opens in a new tab)

Aziz Sheikh

University of Edinburgh, UK

aziz.sheikh@ed.ac.uk

Amir Hussain

Edinburgh Napier University, UK

A.Hussain@napier.ac.uk (this opens in a new tab)

Submission Guidelines

Other links include:
-editorial policies (this opens in a new tab)  -publication policies (this opens in a new tab)  -copyright transfer (this opens in a new tab) -self-archiving (this opens in a new tab)  -OA funding (this opens in a new tab)  -open choice (this opens in a new tab)  -funder compliance (this opens in a new tab)  -read and publish agreements (this opens in a new tab)  -preprint sharing (this opens in a new tab)  -my publication process (this opens in a new tab) -production (this opens in a new tab)  -publication (this opens in a new tab)  -post-publication (this opens in a new tab)  -ORCID (this opens in a new tab)  -Publons (this opens in a new tab)  -article sharing (this opens in a new tab)  -citation alerts (this opens in a new tab)

The outbreak of the novel coronavirus in China (SARS-CoV-2) represents a significant and urgent threat to global health and as such Springer Nature has signed a joint statement (this opens in a new tab) committing to ensure that research findings and data relevant to this outbreak are shared rapidly and openly to inform the public health response and help save lives.  

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