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Data Analytics in Biomedical Engineering and Healthcare

Langue : Anglais

Coordonnateurs : Lee Kun Chang, Roy Sanjiban Sekhar, Samui Pijush, Kumar Vijay

Couverture de l’ouvrage Data Analytics in Biomedical Engineering and Healthcare
Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks.

1. Data analytics applications in biomedical data 2. Predictive Health Analysis 3. Exploration of EHR (Electronic Health Records) using data science 4. Machine Learning and Deep Learning application on medical image analysis 5. Developing Clinical Decision Support System 6. Innovative Classification, Regression Model for predicting various diseases 7. Computational Drug Discovery using State of the Art Unsupervised learning 8. Genome Structure prediction using Predictive modelling 9. Hybrid learning for better medical diagnosis 10. Big data application in healthcare under MapReduce and Hadoop frameworks

1995-To date Full Professor SKK Business School Sungkyunkwan University

Responsible for teaching Business Datamining, MIS (Management Information Systems), and Internet Business Models in undergraduate and graduate. I conduct several director positions for executive programs with Samsung Group. I am the quadruple winner of “The Sungkyunkwan University Outstanding Research Award”. In 2006 I received the university's highest research honor, “The Sungkyunkwan University Fellow Award" in recognition of extraordinary accomplishment in research and scholarship. Accordingly, I was honorably included in the Hall of Fame of the SKK Business School in 2007.
Sanjiban Sekhar Roy is an Associate Professor in the School of Computer Science and Engineering, Vellore Institute of Technology. He joined VIT in the year 2009 as an Asst. Professor. His research interests include Deep Learning and advanced machine learning. He has published around 50 articles in a reputed international journal (with SCI impact factors) and conferences. He also is editorial board members to a handful of international journals and reviewer to many highly reputed journals such as Neural processing letters, Springer , IEEE Access: The Multidisciplinary Open Access Journal, Computers & Security, Elsevier , International Journal of Advanced Intelligence Paradigms, Inderscience International publishers, International Journal of Artificial Intelligence and Soft Computing, Inderscience International publishers,Ad Hoc Networks, Elsevier, Evolutionary Intelligence, Springer, Journal of Ambient Intelligence and Humanized Computing, Springer, Iranian Journal of Science and Technology, Transactions of Electrical Engineering, Springer. He uses Deep Learning and machine learning techniques to solve many complex engineering problems, especially those are related to imagery. He is specialized in deep convolutional neural networks and generative adversarial network. Dr. Roy also has edited many books with reput
  • Examines the development and application of data analytics applications in biomedical data
  • Presents innovative classification and regression models for predicting various diseases
  • Discusses genome structure prediction using predictive modeling
  • Shows readers how to develop clinical decision support systems
  • Shows researchers and specialists how to use hybrid learning for better medical diagnosis, including case studies of healthcare applications using the MapReduce and Hadoop frameworks

Date de parution :

Ouvrage de 292 p.

19x23.3 cm

Disponible chez l'éditeur (délai d'approvisionnement : 14 jours).

146,54 €

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