NDL2022: Diagnosis of Neurological Disorders based on Deep Learning Techniques |
Website | https://sites.google.com/view/neurological-disorder/home |
Submission link | https://easychair.org/conferences/?conf=ndl2022 |
Abstract registration deadline | February 10, 2022 |
Submission deadline | April 30, 2022 |
CRC Press, Taylor & Francis (USA) invites chapter submission for the book titled Diagnosis of Neurological Disorders based on Deep learning Techniques.
Deep learning has recently been used for the analysis of neuroimages, such as structural magnetic resonance imaging (MRI), functional MRI, and positron emission tomography (PET), and it has achieved significant performance improvements over traditional machine learning in neurological disorders. Several approaches have been developed in recent times to automatically diagnose neurological disorders. These approaches can essentially be split into two types of hand-crafted features and classifier approaches based on standard instruction, respectively. The second solution is focused on completely automatic approaches based on deep learning. The first type uses manually segregated characteristics and is given to classifiers as data. However, in the second category of attributes, parameters may be modified to execute unique training data activities. Deep neural networks do not use hand-crafted features and have successfully been adapted to problems with the diagnosis of neurological disorders.
Submission Guidelines
All chapters must be original and not simultaneously submitted to another journal or conference. The following chapter categories are welcome:
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Research Papers describing new techniques in the field of deep learning based diagnosis of neurological disorder.
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Case Studies describing the real life study in the field of deep learning based diagnosis of neurological disorder.
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Submission Link: https://easychair.org/conferences/?conf=ndl2022
List of Topics (but not limited to)
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Neuroimaging in neurological disorder
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Introduction to Deep learning Techniques based Diagnosis for Neurological Disorders: Comparison, Challenges and Future Scopes (Case study).
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Data pre-processing techniques needed for the deep learning-based diagnosis for neurological disorder.
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Role of Internet-of-Things in neurological disorder: Case study
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Prediction / Detection of Alzheimer’s using deep neural networks
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Parkinson’s prediction / detection using deep neural networks
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Best deep learning model selection for the diagnosis for Alzheimer’s / Parkinson’s disease
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Deep neural networks to detect early neurodegenerative disorders disease signal
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Deep learning techniques to identify most effective treatment / therapy for neurodegenerative disorders
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Application of deep learning approaches to development and implementation of treatments for neurodegenerative disorders: Case study
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Challenges and future aspects of deep learning approaches to development and implementation of treatments for neurodegenerative disorders: Case study
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Prediction / Detection of Autism spectrum disorder using deep neural networks
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Schizophrenia prediction / detection using deep neural networks
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Best deep learning model selection for the diagnosis of autism spectrum disorder / Schizophrenia disease
Important Dates
Abstract submission deadline: 10th February 2022
Chapter submission Deadline: 30th April 2022
Review notification: 30th May 2022
Revised chapter submission: 15th June 2022
Final decision notification: 30th June 2022
Submission of Final Chapters to Publisher: 15th July 2022
Publication
This book chapters will be published by CRC Press, Taylor & Francis (USA).
Key Points for Full Chapter
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Each article length may be about 12 to 15 pages.
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Each chapter should consist of Abstract, Introduction, Proposed Method, Results and Discussion, Conclusion and References.
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For plagiarism checking, use only Turnitin or Ithenticate. Chapter plagiarism percentage should be less than 12%.
Benefits of authors
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There is NO processing/publication charge.
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CRC press will provide each corresponding author with one electronic copy free of cost.
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Worldwide circulation through CRC Press.
Contact
All questions about submissions should be emailed to Dr. Jyotismita Chaki, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India. Email: jyotismita@vit.ac.in.