Call for Papers: Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis

Summary and Scope

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.

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.

The main topics include, but are not limited to, the following:

• DL for biomedical signal analysis and processing
• DL for medical image analysis and processing
• DL for diseases detection and diagnosis
• DL for pandemics detection and forecasting
• DL for biometrics
• DL in biomedical engineering
• DL for health informatics
• DL for brain-computer interfaces
• DL for neural rehabilitation engineering
• Related applications

Important Dates:
Submission deadline: August 31, 2023
Reviewing deadline: October 15, 2023
Author revision deadline: November 15, 2023
Final notification date: December 15, 2023

Guest editors
Prof. Larbi Boubchir (Lead GE) - University of Paris 8, France
Email: Larbi.boubchir@univ-paris8.fr

Prof. Elhadj Benkhelifa - Staffordshire University, UK
Email: Benkhelifa@staffs.ac.uk

Prof. Jaime Lloret - Universitat Politecnica de Valencia, Spain
Email: jlloret@dcom.upv.es

Prof. Boubaker Daachi - University of Paris 8, France
Email: boubaker.daachi@univ-paris8.fr

Submission Guidelines:
Authors should prepare their manuscript according to the Instructions for Authors available from the Multimedia Tools and Applications website. Authors should submit through the online submission site at https://www.editorialmanager.com/mtap/default.aspx 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.