posted by organizer: PeerJ || 2714 views || tracked by 3 users: [display]

Understanding Brain Disorders 2022 : Deep Learning Techniques for Understanding Brain Disorders


When N/A
Where N/A
Submission Deadline Dec 2, 2022
Categories    artificial intelligence   data mining   machine learning   neural networks

Call For Papers

The brain is one of the most complex organs of the human body. Modern understanding of brain disorders is shaped by multiple non-invasive modalities of data that can be acquired from the human brain, such as EEG, fMRI, PET and fNIRS. Due to the high dimensional nature of these data, understanding patterns in the data and their discriminability across disorders has been a challenge. The advent of Deep learning (DL) models has begun to address this challenge, through pattern recognition, classification, detection, diagnosis, augmentation and segmentation. The cross-pollination of ideas from neuroscience, neurology, psychiatry, neuroimaging and computer science is required for this budding field to attain its full potential.

The purpose of this Special Issue is to showcase research where ideas from deep learning within the field of engineering and computer science are used to understand brain function in the healthy brain (neuroscience) as well as those in neurological and psychiatric brain disorders with the help of neuroimaging data. Applications to neurological disorders include (but are not limited to) Alzheimer's Disease and Dementia, movement disorders including Parkinson's Disease, Stroke, Epilepsy, Amyotrophic Lateral Sclerosis, Brain Injury and Brain Tumours while psychiatric disorders include Schizophrenia spectrum, Autism spectrum, ADHD, Depression, PTSD, eating disorders, anxiety disorders, etc.

Researchers are encouraged to submit manuscripts related to classification, regression, detection, diagnosis, prediction of treatment outcomes, augmentation or segmentation methods based on DL for publication. Approaches to explainable AI, which enable a scientific understanding of features in the data (and hence aspects of brain function) that are most important for driving the model’s prediction are very much encouraged. This special issue especially welcomes submissions that depict the end-to-end technological viewpoint that uses automated informatics systems to solve single or multiple cases of healthcare advancements.

Related Resources

DVU 2023   Deep Video Understanding Grand Challenge, ACM MM 2023
ICDM 2023   International Conference on Data Mining
EAICI 2024   Explainable AI for Cancer Imaging
JCRAI 2023-Ei Compendex & Scopus 2023   2023 International Joint Conference on Robotics and Artificial Intelligence (JCRAI 2023)
JCICE 2024   2024 International Joint Conference on Information and Communication Engineering(JCICE 2024)
EAIH 2024   Explainable AI for Health
BOES 2023   Bio-inspired Optimization in Engineering and Sciences
IEEE Xplore-Ei/Scopus-CCCAI 2023   2023 International Conference on Communications, Computing and Artificial Intelligence (CCCAI 2023) -EI Compendex
KDLSBM 2023   Knowledge-based Deep Learning System in Bio-Medicine
AAIMLB 2023   Application of Artificial Intelligence and Machine Learning in Biology