AIND 2020: Artificial Intelligence for Neurological Disorders |
Submission link | https://easychair.org/conferences/?conf=aind2020 |
Abstract registration deadline | November 13, 2020 |
Submission deadline | January 15, 2021 |
The novel applications of Artificial Intelligence and Big Data Analytics for Neurological disease research can be regarded as an emerging field in computer science, medicine, biology application, biomedical engineering, and artificial intelligence. The use of various techniques of artificial intelligenceand data mining approaches are being successfully applied to different fields of life sciences for the past 20 years. Medicine is one of the most appropriate application domains for these techniques since they facilitate model diagnostic information based on causal and/or statistical data and therefore reveal hidden dependencies between symptoms and illnesses .The book will play a vital role in improvising human life to a great extent. All the researchers and practitioners will be highly benefited those are working in field of biomedical engineering, health informatics, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics
Submission Guidelines
All Chapterss must be original and not simultaneously submitted to another journal or conference. The following Chapters categories are welcome:
Chapter 1:
Artificial intelligence-Based Early Detection of neurological Disease Using Non-Invasive Method Based on Speech Analysis
Chapter 2
An Intelligent Diagnostic approach for Epileptic Seizure Detection and Classification Using Machine Learning
Chapter 3
Classification of neurodegenerative disorders using machine learning techniques.
Chapter 4
Computational Methods for Translational Brain-Behaviour Analysis
Chapter 5
Brain Imaging Techniques for Brain Computer Interfaces using Deep Learning
Chapter 6
Ensemble sparse intelligent mining techniques for cognitive disease.
Chapter 7
Neurological Image Characterization and Radio genomics using Machine Learning Techniques
Chapter 8
Ontological Dimensions of Cognitive-Neural Mappings
Chapter 9
Feature Classification and Extraction of Neurological Medical Data Using Machine Learning Techniques
Chapter 10
Clinical applications of deep learning in neurology and its enhancements with future directions
Chapter 11
Cognitive therapy for brain diseases using deep learning models
Chapter-12
Computational Models of Consciousness-Emotion Interactions.
Chapter-13
Interdisciplinary perspectives on the development, integration, and application of cognitive ontologies
Chapter-14
Neural signalling and communication using Machine learning
Chapter-15
New trends in deep learning for neuroimaging analysis and disease prediction
Chapter 16
Clinical applications of deep learning in neurology and its enhancements with future predictions
Chapter 17
Cognitive therapy for brain diseases using artificial intelligence models.
Chapter 18
Prevention and diagnosis of neurodegenerative diseases using machine learning models.
The Chapters which will contain around 10000 words with less than 10% plagiarism
- Posters describing Abstract submission of around 500 words
Contact
neuro.elsevier2020@gmail.com
skpani.india@gmail.com