CIML2021: Computational intelligence and Machine Learning approaches in the field of Biomedical Engineering and Health Care Systems |
Website | https://www.gitam.edu/ |
Submission link | https://easychair.org/conferences/?conf=ciml2021 |
Abstract registration deadline | February 15, 2021 |
Submission deadline | March 15, 2021 |
Submission deadline of final document | May 15, 2021 |
Introduction:
Computational intelligence and machine learning-based approaches in Biomedical engineering is an emerging technology that is significant in computer-aided diagnosis and medical analysis. With the advancement in biomedical engineering fields through deep learning and soft-computing mechanisms, there is a remarkable impact on the outcomes that would assist the physicians in ease of diagnosis, treatment, and surgical planning. Furthermore, with multidisciplinary mechanisms in the biomedical field, physicians can successfully deal with critical health care problems that are recognized through medical imaging technologies like X-Ray, CT(Computed Tomography), MRI(Magnetic Resonance Imaging), PET(Positron Emission Tomography), advance prediction of abnormality through big data analytics, use of Internet of Things and semantic technology for the health care monitoring and many others. Broadly it consists of various phases of medical imaging and medical data analytics that include image acquisition, image enhancement, complicated hidden feature extraction, Image segmentation, post-processing of the image for abnormality identification and incorporation of evolutionary computation, fuzzy logic, Natural Computation, Artificial Neural Network, Classification techniques for the better analyzing and formulating outcome.
About the Book:
This book incorporates remarkable and outstanding contributions in computer-aided diagnosis and biomedical analytics that can benefit diverse areas of biomedical engineering, taking into account biomedical imaging, Computational Medicine, Diagnosis, Health informatics, implants, and Medical Devices, and Healthy Systems Engineering. It provides a comprehensive study of various machine-learning algorithms and deep neural network-based approaches in biomedical engineering. It would be focusing on models, methods, and applications in Image Analysis, Multimodal Imaging Mechanisms, Assistive Technology, Telemedicine, and Interdisciplinary approaches for the future horizon. It serves as an absolute information provider of the multidisciplinary mechanisms used in Biomedical Engineering and its outcomes.
Topics of Interest:
· A survey of various existing systems and applications of Biomedical engineering.
· Soft Computing Techniques in Biomedical Engineering.
· Biomedical Imaging Techniques using Artificial intelligence and Machine Learning.
· Optimization and Evolutionary algorithms in the field of biomedical engineering.
· Automated approaches for assessment of the severity of the abnormality.
· Big data Analytics in the biomedical system for predictive analysis.
· Self-Learning and Weakly trained algorithms for predictive analysis of ailments.
· Semantic technology in Biomedical engineering.
· Deep Learning-based mechanism for medical diagnosis.
· Medical image processing for abnormality recognition through CT/MRI/PET scans.
· Handling and analysis of multidimensional imaging.
· Volumetric estimations from 2D/3D imaging and precision biomedical engineering.
· eHealth system and Telemedicine.
· Novel approaches and feasibility study of robotic surgery.
· Case studies and their solutions through practical implications.
· Storage and Compression of medical-related data.
· Health monitoring through IoT.
· Blockchain technology in Biomedical Engineering.
· Security services and privacy preservation in Biomedical related data Feasibility studies and future challenges in Biomedical Engineering.
Editors:
Prof. Dr. Norita Md Norwawi, Universiti Sains Islam Malaysia, Nailai, Malaysia
Dr. P Naga Srinivasu, GITAM Institute of Technology, GITAM Deemed to be University, India
Prof. Dr. Sheng Lung Peng, National Dong Hwa University, Hualien, Taiwan
Prof. Dr. Azuraliza Abu Bakar, Universiti Kebangsaan,Malaysia
Important Dates:
Abstract Submission: 15th Feb 2021 |
Notification to Authors: 28th Feb 2021 |
Full Chapter Submission: 15th March 2021 |
Review Notification: 30th March 2021 |
Revised Chapter Submission: 15th April 2021 |
Final Submission Due: 30th Feb 2021 |
Targeted Audience:
The book is undoubtedly an aide for the people from the industries, professionals, academicians, and an imperative first choice for researchers and post graduate students involved in Biomedical Engineering, Medical Image Processing, Machine Learning Algorithms, and Computational Intelligence systems directly or indirectly. Further, this book may be recommended for incorporating in the regular curriculum for the graduate courses in Computer Science Engineering, Biomedical Engineering, and Artificial Intelligence-based engineering courses. All the book chapters are self-sufficient and independent that gives a complete framework of the problem formulation to its proposed solution and outcome.
Keywords: Soft Computing, Machine Learning, Neural Networks, Deep Learning, Optimization techniques, Evolutionary algorithms, Semantic Technology, Medical Imaging, Computational intelligence
Contact/Submission:
You may express your interest for contribution or regarding any queries about submissions should be emailed to the editors:
Dr. Parvathaneni Naga Srinivasu, Assistant Professor, Department of Computer Science and Engineering, GITAM Institute of Technology, GITAM Deemed to be University,Visakhapatnam-530045, India
Email: parvathanenins@gmail.com; nparvath@gitam.edu;
Please let us know if you are interested in submitting a proposal for this book.
Note: There is no submission/publication fees.
We are trying to approaching few selected researchers for this book and Please accept our apologies if you have received multiple copies of this mail.