This book is an essential guide to the constantly changing environment of embedded systems in healthcare in a world where the convergence of technology and healthcare is becoming increasingly important. It further explains different scenarios corresponding to the latest technologies in the healthcare system for early diagnosis, enhanced treatment, and cure of diseases, including remote patient monitoring, cardiac monitoring, and deep learning for remediation.
Features:
* Emphasizes how embedded systems contribute to clinical care by facilitating personalized treatment and informed decision-making for healthcare professionals.
* Highlights the role of embedded systems in tracking treatment progress, enabling healthcare professionals to monitor patient responses and adjust treatment plans accordingly.
* Explores the application of embedded systems in remote patient monitoring, allowing for continuous health monitoring outside traditional healthcare settings.
* Presents the integration of deep learning and telecommunication technology with embedded systems, optimizing their efficiency and utilization in biomedical applications.
* Offers insights into future prospects for advancing biomedical applications through embedded systems, providing a roadmap for further innovation and development in the field.
This reference work is useful for scholars and professionals interested in the applications and optimization of emerging smart technologies in the field of healthcare.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Academic and Postgraduate
Illustrationen
64 s/w Abbildungen, 9 s/w Photographien bzw. Rasterbilder, 55 s/w Zeichnungen, 11 s/w Tabellen
11 Tables, black and white; 55 Line drawings, black and white; 9 Halftones, black and white; 64 Illustrations, black and white
Maße
Höhe: 240 mm
Breite: 161 mm
Dicke: 21 mm
Gewicht
ISBN-13
978-1-032-83191-6 (9781032831916)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Rishabha Malviya completed B. Pharmacy from Uttar Pradesh Technical University and M. Pharmacy (Pharmaceutics) from Gautam Buddha Technical University, Lucknow Uttar Pradesh, India. His PhD (Pharmacy) work was in the area of Novel formulation development techniques. He has 14 years of research experience and presently working as Associate Professor in the Department of Pharmacy, School of Medical and Allied Sciences, Galgotias University, India since past 11 years. His area of interest includes formulation optimization, AI for healthcare applications, nanoformulation, targeted drug delivery, localized drug delivery and characterization of natural polymers as pharmaceutical excipients. He has authored more than 150 research/review papers for national/international journals of repute. He has 58 patents (19 grants, 38 published, 1 filed) and publications in reputed National and International journals with total of more than 300 cumulative impact factor. He has authored/edited/editing 78 books and authored 145 book chapters. His name has included in word's top 2% scientist list for the year 2020 and 2021 by Elsevier BV and Stanford University. He is Reviewer/Editor/Editorial board member of more than 50 national and international journals of repute.
Selcan Karakus is currently an Associate Professor in the Department of Chemistry, at Istanbul University-Cerrahpasa (IUC), Turkiye. She received her Master of Science degree in physical chemistry from Istanbul University (IU) in 2006, and her Ph.D. in physical chemistry from IU in 2011. She has been a visiting researcher at the University of Massachusetts, Department of Polymer Science and Engineering. She has research experience in drug carrier systems, nanoparticles, nanocomposites, nano-emulsion self-assembled polymeric nanostructures, and copolymer blends. She has worked on a variety of projects funded by IUC and has published several research articles and book chapters.
Mukesh Roy obtained his Doctor of Philosophy in Mechanical Engineering from South Dakota State University, USA, in 2021. His research endeavors concentrated on the study of the mechanics of vascular tissue to employ it as a template for engineering design and flexible biocomposites. After completing his Ph.D., Dr. Roy went on to complete a Postdoctoral Fellowship at the National Science Foundation's Engineering Research Center for Cellular Metamaterials (CELL-MET), Florida International University, USA in the year 2023. During this fellowship, Dr. Roy worked on the characterization of stem cell-laden cardiovascular patches, specifically focusing on myocardial tissue at multiple scales. Currently, Dr. Roy serves as a Clinical Researcher and Biostatistician at the Office of Clinical Research in Baptist Health South Florida-Miami, USA. Dr. Roy has a research experience of 8+ years and has authored and published over 24 peer-reviewed scientific articles, conference papers, 2 book chapters, and 40+ abstracts. In addition, Dr. Roy has filed 6 patents, with one granted in the USA and 5 published in India. Dr. Roy has received 6 awards and 3 fellowships for his research, creativity, and innovations. Furthermore, Dr. Roy serves as an editorial board member and reviewer for various journals and conferences in biomaterials, computational biomechanics, biomedical devices, and public health research. Dr. Roy's research is highly interdisciplinary, and his interests include biomedical devices, clinical trials, regenerative tissues, biomaterials, and bioinspired design.
Herausgeber*in
Galgotias Uni.
1. Introduction to Embedded System in Healthcare: Operational Environments in Healthcare Settings 2. Embedded Systems in the medical field: pros. and cons. 3. Automation of in the medical field: pros. and cons. 4. Embedded system in developing imaging devices 5. Deep Learning of Telecommunication Technology for The Efficient Utilization of Embedded Systems 6. Role of Embedded Systems in Diagnosis and Decision-Making for Better Treatment 7. Enhancing Remote Healthcare: Integration of ATOM ECG with eSanjeevani 8. Artificial Intelligence in Embedded Systems for Biomedical Applications 9. Embedded systems in metabolic bariatric surgery: from telemonitoring to deep learning applications. 10. Integration of Machine Learning Techniques with Multi-Criteria Decision-Making for a Better Treatment 11. Embedded systems in developing advanced strategies in healthcare management 12. Human Health Status Detection from the Tongue Image Using Embedded Image Processing
