Book:DLforBMA 2020: Deep Learning for Biomedical Applications |
Abstract registration deadline | June 30, 2020 |
Submission deadline | August 31, 2020 |
Call for Chapters
Deep Learning for Biomedical Applications
Edited by Utku Kose, Omer Deperlioglu, Jude Hemanth
to be published by CRC Press
Since its first appearance in the scientific arena, Artificial Intelligence has taken many steps away. Especially after start of the 21st century, it has improved its influence in even modern daily life and gained more momentum to design the future of the humankind. Thanks to also rapid developments in supportive technologies surrounding it, the field of Artificial Intelligence is now the most effective tool for dealing with real world problems. From natural sciences to social sciences, it is possible to see effective use of intelligent systems in all fields. Majority of such intelligent systems are employed in the context of the fields, which are focused on especially improving quality of our life. At this point, the field of medical has a vital place in our life so that there has been a remarkable research effort by Artificial Intelligence for developing effective and efficient solutions for the problems in it. Today, biomedical oriented problems take scientists’ interest so every kind of approaches, methods and techniques of Artificial Intelligence is used to develop innovative solutions such as automated diagnosis systems, information discovery environments and even personal healthcare applications. Here, as an important sub-field of Artificial Intelligence, Machine Learning provides effective techniques for learning from samples and experiences to derive accurate solutions at the end. On the other hand, Deep Learning, which is the advanced form of Machine Learning, is in rise recently as it provides very effective performances in the field of medical.
Objective of this edited book is to gather the most recent research efforts on using Deep Learning based solutions for the problems of biomedical. As the newest face of Machine Learning, Deep Learning employs advanced, larger forms of traditional Artificial Neural Networks to deal with huge amount of data and provide better results by achieving different complex tasks at once and improving previously reported results by other intelligent systems. In the context of biomedical applications, use of Deep Learning can be associated with computer-aided diagnosis, data synthesis, medical image analysis, medical image registration and many other solution scopes. Because it is a powerful tool to solve many difficult problems and ensure revolutionary improvements for former achievements, Deep Learning is a trendy topic for the scientists and even doctors. Effective Deep Learning techniques such as Convolutional Neural Networks, Auto-encoders, and Long Short-Term Memory have already given many important outputs for remarkable problems of biomedical. According to alternative research works done so far, it is also possible to develop hybrid systems by combining Deep Learning techniques and other data processing approaches to have more and more effective solutions. Employment of Deep Learning has even resulted to designing diagnosis systems, which can diagnose-predict diseases better than doctors. So, use of Deep Learning is a triggering factor to design future of medical in which humans and intelligent systems can both work together for better research and service efforts.
Submission Guidelines
All full chapter submissions should be done by e-mail to: utkukose@gmail.com
All papers must be original and not simultaneously submitted to another book project, journal or conference.
Please use the template and the related files from that link: http://utkukose.com/CRC_BookDLforBMA_template_etc.zip while preparing your full chapter.
Submissions can be done till the following date (before preparing full chapter, it may appropriate to send brief proposal / abstract for pre-acceptance by the editors):
- Full Chapter Submission: 31 August 2020
Important: Similarity Rate for the full chapter should be max. 25%. The authors able to get similarity report are suggested to send the similarity reports with other files.
List of Topics (as not limited to)
- Disease Diagnosis with Deep Learning,
- Medical Image Analysis with Deep Learning,
- Medical Image Registration with Deep Learning,
- Medical Data Synthesis with Deep Learning,
- Genomics with Deep Learning,
- Patient Care and Treatment with Deep Learning,
- Hybrid Intelligent Deep Learning Oriented Systems for Biomedical,
- Deep Learning Oriented Robotics for Biomedical,
- Deep Learning Based Autonomous Biomedical Solutions,
- Specific Use of Deep Learning Techniques (CNN, LSTM…etc.) for Biomedical,
- Compare of Deep Learning with Traditional Solutions for Biomedical,
- ...etc.
Editors
- Utku Kose, PhD. (Suleyman Demirel University, Turkey)
- Omer Deperlioglu, PhD. (Afyon Kocatepe University, Turkey)
- D. Jude Hemanth, PhD. (Karunya University, India)
Publication
'Deep Learning for Biomedical Applications' will be published by CRC Press, a member of Taylor & Francis Group, UK.
Contact
All questions about submissions should be emailed to: utkukose@gmail.com