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<p>[Apologies if you receive multiple copies of this CFP] <br>
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<p> </p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;
mso-outline-level:1"><b><span style="font-size: 14pt;"
lang="EN-US">Call for Papers: <span style="color:#0070C0">Emerging
Trends and Applications of Deep Learning for Biomedical
Data Analysis </span></span></b></p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span
style="color:blue;mso-ansi-language:EN-US" lang="EN-US"><a
href="https://www.springer.com/journal/11042/updates/24678968"
class="moz-txt-link-freetext" moz-do-not-send="true">https://www.springer.com/journal/11042/updates/24678968</a></span></p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b>Summary
and Scope</b></p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">Nowadays,
Deep learning (DL) becomes an attractive research topic for many
researchers from academia and industry communities. Indeed, DL
algorithms have demonstrated their ability to train learning
models for large-volume data as well as their performances
compared to conventional machine learning algorithms. The DL
approaches were studied and applied to resolve several complex
problems in various research domains, such as computer vision,
biometrics, brain-computer interfaces, robotics, and other
fields. Several architectures of DL (e.g., supervised,
unsupervised, reinforcement, and beyond) have been proposed in
the literature as solutions for various research problems in
data analysis related to detection, classification, recognition,
prediction, decision-making, etc.<br>
<br>
The special issue aims to solicit original research work
covering novel algorithms, innovative methods, and meaningful
applications based on the DL that can potentially lead to
significant advances in biomedical data analysis.</p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">The
main topics include, but are not limited to, the following:<br>
<br>
• DL for biomedical signal analysis and processing<br>
• DL for medical image analysis and processing<br>
• DL for diseases detection and diagnosis<br>
• DL for pandemics detection and forecasting<br>
• DL for biometrics<br>
• DL in biomedical engineering<br>
• DL for health informatics<br>
• DL for brain-computer interfaces<br>
• DL for neural rehabilitation engineering<br>
• Related applications</p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><br>
</b></p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b>Important
Dates:</b><br>
Submission deadline: August 31, 2023<br>
Reviewing deadline: October 15, 2023<br>
Author revision deadline: November 15, 2023<br>
Final notification date: December 15, 2023</p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><br>
</b></p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b>Guest
editors</b><br>
Prof. Larbi Boubchir (Lead GE) - University of Paris 8, France<br>
Email: <a class="moz-txt-link-abbreviated
moz-txt-link-freetext"
href="mailto:Larbi.boubchir@univ-paris8.fr"
moz-do-not-send="true">Larbi.boubchir@univ-paris8.fr</a><br>
<br>
Prof. Elhadj Benkhelifa - Staffordshire University, UK<br>
Email: <a class="moz-txt-link-abbreviated
moz-txt-link-freetext" href="mailto:Benkhelifa@staffs.ac.uk"
moz-do-not-send="true">Benkhelifa@staffs.ac.uk</a><br>
<br>
Prof. Jaime Lloret - Universitat Politecnica de Valencia, Spain<br>
Email: <a class="moz-txt-link-abbreviated
moz-txt-link-freetext" href="mailto:jlloret@dcom.upv.es"
moz-do-not-send="true">jlloret@dcom.upv.es</a><br>
<br>
Prof. Boubaker Daachi - University of Paris 8, France<br>
Email: <a class="moz-txt-link-abbreviated
moz-txt-link-freetext"
href="mailto:boubaker.daachi@univ-paris8.fr"
moz-do-not-send="true">boubaker.daachi@univ-paris8.fr</a><br>
<br>
<b>Submission Guidelines:</b><br>
Authors should prepare their manuscript according to the
Instructions for Authors available from the Multimedia Tools and
Applications <a href="https://www.springer.com/journal/11042/"
target="_blank" moz-do-not-send="true"><span
style="mso-ansi-language:EN-US" lang="EN-US">website</span></a>.
Authors should submit through the online submission site at <a
href="https://www.editorialmanager.com/mtap/default.aspx"
target="_blank" moz-do-not-send="true"><span
style="mso-ansi-language:EN-US" lang="EN-US">https://www.editorialmanager.com/mtap/default.aspx</span></a>
and select “SI 1239 - Emerging Trends and Applications of Deep
Learning for Biomedical Data” when they reach the “Article Type”
step in the submission process. Submitted papers should present
original, unpublished work, relevant to one of the topics of the
special issue. All submitted papers will be evaluated on the
basis of relevance, significance of contribution, technical
quality, scholarship, and quality of presentation, by at least
three independent reviewers. It is the policy of the journal
that no submission, or substantially overlapping submission, be
published or be under review at another journal or conference at
any time during the review process.</p>
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