Advanced Prognostic Predictive Modelling in Healthcare Data Analytics -

Advanced Prognostic Predictive Modelling in Healthcare Data Analytics (eBook)

eBook Download: PDF
2021 | 1st ed. 2021
XIV, 311 Seiten
Springer Singapore (Verlag)
978-981-16-0538-3 (ISBN)
Systemvoraussetzungen
181,89 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen

This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence.  The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.



Dr. Sudipta Roy has received his Ph.D. in Computer Science & Engineering from the Department of Computer Science and Engineering, University of Calcutta. He is an author of more than forty publications in refereed national/international journals and conferences including IEEE, Springer, Elsevier and many others. He is an author of one book and many book chapters. He holds an US patent in medical image processing and filed an Indian patent in smart agricultural system. He has served as a reviewer of many international journals including IEEE, Springer, Elsevier, IET and many others, and international conferences. He has served as an international advisory committee member and a program committee member of AICAE-2019, INDIACom-2019, CAAI 2018, ICAITA-2018, ICSESS-2018, INDIACom-2018, ISICO-2017, AICE-2017 and many more conferences. He is serving as Associate Editor of IEEE Access, IEEE and International Journal of Computer Vision and Image Processing (IJCVIP), IGI Global Journal. He has more than five years of experience in teaching and research. His fields of research interests are healthcare image analysis, image processing, steganography, artificial intelligence, big data analysis, machine learning and big data technologies. Currently, he is working at PRTTL, Washington University in St. Louis, Saint Louis, MO, USA. 

Dr. Lalit Mohan Goyal has completed Ph.D. from Jamia Millia Islamia, New Delhi, in Computer Engineering, M.Tech. (Honours) in Information Technology from Guru Gobind Singh Indraprastha University, New Delhi, and B.Tech. (Honours) in Computer Engineering from Kurukshetra University, Kurukshetra. He has 16 years of teaching experience in the area of theory of computation, parallel and random algorithms, distributed data mining & cloud computing. He has completed a project sponsored by Indian Council of Medical Research, Delhi. He has also published research papers in SCI indexed & Scopus indexed journals and conferences. He is a reviewer of many reputed journals & conferences also. Presently, he is working at J. C. Bose University of Science & Technology, YMCA, Faridabad, in the Department of Computer Engineering.

Dr. Mamta Mittal graduated in Computer Science & Engineering from Kurukshetra University Kurukshetra in 2001 and received master's degree (Honours) in Computer Science & Engineering from YMCA, Faridabad. She has completed her Ph.D. from Thapar University Patiala in Computer Science and Engineering. She has been teaching from the last 16 years with emphasis on data mining, machine learning, soft computing and data structure. She is a lifetime member of CSI. She has published and communicated number of research papers in SCI, SCIE and Scopus indexed Journals and attended many workshops, FDPs and Seminars. She has filed two patents - one is on human surveillance system and another is on wireless copter for explosive handling and diffusing. Presently, she is working at G.B. Pant Government Engineering College, Okhla, New Delhi (under Government of NCT Delhi), and supervising Ph.D. candidates of GGSIPU (Guru Gobind Singh Indraprastha University), Dwarka, New Delhi. She is Main Editor of the Book entitled 'Data Intensive Computing Application for Big Data' published by IOS Press, Netherland, and another Book entitled 'Big Data Processing Using Spark in Cloud' by Springer. She is Managing Editor of International Journal of Sensors, Wireless Communications and Control Published by Bentham Science. She is working on DST approved Project 'Development of IoT based hybrid navigation module for mid-sized autonomous vehicles' and Handing Pradhan Mantri YUVA project for Entrepreneur Cell Activity as Faculty Coordinator/Representative from G.B. Pant Government Engineering College. She is a reviewer of many reputed journals, chaired number of conferences and delivered invited talks.


This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence.  The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.
Erscheint lt. Verlag 22.4.2021
Reihe/Serie Lecture Notes on Data Engineering and Communications Technologies
Zusatzinfo XIV, 311 p. 137 illus., 106 illus. in color.
Sprache englisch
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Statistik
Medizin / Pharmazie
Technik
Schlagworte classification • Deep Neural Network • Healthcare • Image and Data Analysis • Predictive Modelling • Prognostic Modelling • Segmentation • supervised learning
ISBN-10 981-16-0538-6 / 9811605386
ISBN-13 978-981-16-0538-3 / 9789811605383
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 10,9 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich
der Praxis-Guide für Künstliche Intelligenz in Unternehmen - Chancen …

von Thomas R. Köhler; Julia Finkeissen

eBook Download (2024)
Campus Verlag
38,99
Wie du KI richtig nutzt - schreiben, recherchieren, Bilder erstellen, …

von Rainer Hattenhauer

eBook Download (2023)
Rheinwerk Computing (Verlag)
24,90