Data Analytics in Biomedical Engineering and Healthcare

Häftad, Engelska, 2020

Av Kun Chang Lee, Sanjiban Sekhar Roy, Pijush Samui, Vijay Kumar, Sungkyunkwan University) Lee, Kun Chang (Professor, SKK Business School, Vellore Institute of Technology) Roy, Sanjiban Sekhar (School of Computer Science and Engineering, India) Samui, Pijush (Associate Professor, Dept. of Civil Engineering, National Institute of Technology Patna, Patna, Bihar, India) Kumar, Vijay (Assistant Professor, Department of Physics, National Institute of Technology Srinagar, Jammu and Kashmir

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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.

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

Produktinformation

Utgivningsdatum2020-10-16
Mått191 x 235 x undefined mm
Vikt700 g
FormatHäftad
SpråkEngelska
Antal sidor292
FörlagElsevier Science
ISBN9780128193143

Tillhör följande kategorier

Biokemisk teknik inom Naturvetenskap och teknik
Biomedicinsk teknik inom Medicin

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. Dr. Sanjiban Sekhar Roy (Member, IEEE) is a distinguished academic and researcher, currently serving as a Professor in the School of Computer Science and Engineering at Vellore Institute of Technology (VIT). He earned his Ph.D. in 2016 from VIT, and from 2019 to 2020, he served as an Associate Researcher at Ton Duc Thang University, Vietnam. With an extensive academic career, Dr. Roy has published over 80 peer-reviewed articles in renowned international journals and conferences, making significant contributions to the fields of deep learning, advanced machine learning, and artificial intelligence. He has authored and co-authored several books published by Elsevier and CRC Press. In addition to these, he has edited 10 books with prestigious international publishers, demonstrating his expertise in computer science and technology. Dr. Roy holds two patents and is an active member of various doctoral committees, providing valuable guidance to Ph.D. scholars. He has mentored numerous postgraduate and undergraduate students, helping them navigate their research projects and academic pursuits. Beyond his research and teaching, Dr. Sanjiban Sekhar Roy has served as an editorial member for several highly respected journals and has edited special issues for prominent publications in his field. His research and academic contributions have been recognized globally, earning him the prestigious “Diploma of Excellence Award for academic research from the Ministry of National Education, Romania, in 2019. Dr. Roy’s work continues to push the boundaries of artificial intelligence, particularly in deep learning and machine learning. His contributions to the academic community and his leadership in research have made a lasting impact on the advancement of these transformative technologies.Dr. Samui is an Associate Professor in the Department of Civil Engineering at NIT Patna, India. He received his PhD in Geotechnical Engineering from the Indian Institute of Science Bangalore, India, in 2008. His research interests include geohazard, earthquake engineering, concrete technology, pile foundation and slope stability, and application of AI for solving different problems in civil engineering. Dr. Samui is a repeat Elsevier editor but also a prolific contributor to journal papers, book chapters, and peer-reviewed conference proceedings. Dr. Vijay Kumar received M.Sc. degree in Electronics from the Magadh University, India 2003. He has completed a M.Tech degree in Microwave remote sensing systems from BIT Mesra, Ranchi, in 2005, and completed PhD from IIT Bombay, Mumbai in 2011 in Microwave Remote sensing. He worked as DST Govt. of India sponsored scientist/principal Investigator at CSRE, IIT Bombay during 2009 to 2013. He has been a visiting researcher at Earth observation Group, Northern Research Institute (NORUT) during 2009-2010. Presently, Kumar is working as Associate professor at School of Electronics Engineering, VIT University, Vellore TN, India from 2013 till date.

1. Data analytics applications in biomedical data2. Predictive Health Analysis3. Exploration of EHR (Electronic Health Records) using data science4. Machine Learning and Deep Learning application on medical image analysis5. Developing Clinical Decision Support System6. Innovative Classification, Regression Model for predicting various diseases7. Computational Drug Discovery using State of the Art Unsupervised learning8. Genome Structure prediction using Predictive modelling9. Hybrid learning for better medical diagnosis10. Big data application in healthcare under MapReduce and Hadoop frameworks