SPECIAL SESSION on Advances in Deep Learning for Biomedical Data Analysis

Scope and Topics

Biomedical data analysis involves the treatment of the physiological electrical activities measured using sensors placed on a living thing, also the medical imaging, allowing it to provide a useful process for abnormality detection and diagnosis purposes. Recently, Deep Learning (DL) has received a great attention to solve difficult and complex problems related to biosignal and medical image processing, where the traditional signal/image processing algorithms and conventional machine learning techniques have shown their limitations to solve such problems. Indeed, the recent advances in this area have brought impressive progress to solve several practical and difficult problems in many fields including medicine, healthcare, e-health, neuroscience, brain-computer interface (BCI), neurofeedback, robotics, robotic exoskeletons, and biometrics, etc. In this context, advanced DL models, have shown their effectiveness to resolve various problems of detection, classification, clustering, prediction, segmentation, diagnosis, etc.; thus, becomes useful solutions to be investigated more for other open problems.

The aim of this special session is to bring together researchers and scientists in the fields of biomedical signal and image processing, artificial intelligence and artificial learning, to present and discuss the recent advances in DL algorithms and methods applied for biomedical data processing.

The main topics that are of interest to this special session include, but are not limited to:

- DL for biomedical signal analysis and processing (e.g., EEG, ECG, EMG, EOG, …)
- DL for medical image analysis and processing (e.g., MRI, X-ray, PET scan, CT scan, …)
- DL for diseases detection and diagnosis
- DL for pandemics detection and forecasting
- DL for biometrics
- DL for health informatics
- DL for e-health
- DL for brain-computer interfaces
- Related applications

ORGANIZERS

Larbi Boubchir
Full Professor
University of Paris 8, France

Boubaker Daachi
Full Professor
University of Paris 8, France

SUBMISSION GUIDELINE

Prospective authors are invited to submit complete papers of no more than eight (8) pages in the IEEE two-column conference proceedings format. Please follow the submission guideline from the IJCNN 2025 submission website.

Special session papers are treated the same as regular conference papers. Please specify that your paper is for the Special Session on Advances in Deep Learning for Biomedical Data Analysis.

All the accepted and presented papers will be published on IEEE Xplore Digital Library and indexed by Scopus.

AUTHORS INFORMATIONS

Author instructions: https://2025.ijcnn.org/authors/initial-author-instructions

Paper submission guidelines: https://cmt3.research.microsoft.com/IJCNN2025/

Further information is available at: https://2025.ijcnn.org/

CONTACT
Any inquiries can be directed to Prof. Larbi Boubchir (larbi.boubchir@univ-paris8.fr)