Call for book chapters for the edited book titled as,
"Data Analytics in Biomedical Engineering and Healthcare"
To be published by "ELSEVIER
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Editors :
- Kun Chang Lee
Sungkyunkwan University Myung Ryun 3-53, Chong No-Ku Seoul 110-745
Republic of Korea
- Sanjiban Sekhar Roy
School of Computer Science and Engineering,Vellore Institute of Technology, Vellore, Tamilnadu, Pin: 632014 ,India
- Pijush Samui
Department of Civil Engineering NIT Patna, Patna – 800005 Bihar ,India
- Vijay Kumar
School of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore-632014, TN ,India
Dear Sir,
Greetings!!
We are in the process of editing a forthcoming book publication entitled **** Data Analytics in Biomedical Engineering and Healthcare ****, to be published by Elsevier. We would like to take this opportunity to cordially invite you to submit a quality chapter proposal for consideration in this book.
We are familiar with your research interests and expertise(theory and practice) in the area of Data Analytics/Pattern recognition/Machine Learning/ Deep Learning applications specially on healthcare domain, and we are certain that your contribution on this topic, would make an excellent addition to this book.
The last date of full chapter submission is OCT 15th, 2019. Kindly try to submit one novel modern technique related to health analytics preferably in MS Word(up to 10,000 words).
Feel free to contact us,we remain at your disposal,
Best Regards,
Editors,
You can send chapters to any one of the following email ids.
or
pijushsamui@gmail.com
or
vksacisro@gmail.com
Authors can contribute a quality chapter on the following topics,
- Data analytics applications in biomedical data.
- Predictive Health Analysis.
- Exploration of EHR (Electronic Health Records) using data science.
- Machine Learning and Deep Learning application on medical image analysis.
- Developing Clinical Decision Support System.
- Innovative Classification, Regression Model for predicting various deceases.
- Computational Drug Discovery using State of the Art Unsupervised learning.
- Genome Structure prediction using Predictive modelling.
- Hybrid learning for better medical diagnosis
- Big data application in healthcare under MapReduce and Hadoop frameworks
- Biological and medical applications of microwave and RF systems
- Implantable and wearable diagnostic and therapeutic systems
- IOT (Internet of Things) in Healthcare
- Smart e-health Gateways
- Wireless communication technologies and wireless power transfer for body-area networking
- Electromagnetic imaging and target detection using DNN/RNN/CNN
- Computational methods for bio-electromagnetics
- Anomaly Detection in Health Data Based data analytics
- Medical RF, MW & MMW Applications and Devices
- Study of Effects of RF and MW on Biological Tissues
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