Advances in Artificial Intelligence, Computation, and Data Science (eBook)
XIV, 369 Seiten
Springer International Publishing (Verlag)
978-3-030-69951-2 (ISBN)
Artificial intelligence (AI) has become pervasive in most areas of research and applications. While computation can significantly reduce mental efforts for complex problem solving, effective computer algorithms allow continuous improvement of AI tools to handle complexity-in both time and memory requirements-for machine learning in large datasets. Meanwhile, data science is an evolving scientific discipline that strives to overcome the hindrance of traditional skills that are too limited to enable scientific discovery when leveraging research outcomes. Solutions to many problems in medicine and life science, which cannot be answered by these conventional approaches, are urgently needed for society.
This edited book attempts to report recent advances in the complementary domains of AI, computation, and data science with applications in medicine and life science. The benefits to the reader are manifold as researchers from similar or different fields can be aware of advanced developments and novel applications that can be useful for either immediate implementations or future scientific pursuit.
Features:
- Considers recent advances in AI, computation, and data science for solving complex problems in medicine, physiology, biology, chemistry, and biochemistry
- Provides recent developments in three evolving key areas and their complementary combinations: AI, computation, and data science
- Reports on applications in medicine and physiology, including cancer, neuroscience, and digital pathology
- Examines applications in life science, including systems biology, biochemistry, and even food technology
Tuan D. Pham is professor and founding director of the Center for Artificial Intelligence at Prince Mohammad Bin Fahd University, Saudi Arabia. His previous position was Professor of Biomedical Engineering at Linkoping University, Sweden. His current research focuses on AI and machine learning methods for image processing, time-series analysis, complex networks, and pattern recognition applied to medicine, biology, and mental health. In 2020, Dr. Pham was selected as Expert in Artificial Intelligence for consultation by the U.S. Food & Drug Administration (FDA) Center for Devices and Radiological Health (CDRH) Network of Digital Health Experts Program (NoDEx).
Hong Yan is currently chair professor of computer engineering at City University of Hong Kong. His research interests include image processing, pattern recognition, and bioinformatics. He has over 600 journal and conference publications in these areas. Professor Yan is IEEE Fellow and IAPR Fellow. He received the 2016 Norbert Wiener Award from the IEEE SMC Society for contributions to image and biomolecular pattern recognition techniques. He is a member of the European Academy of Sciences and Arts.
Dr. Muhammad Waqar Ashraf is professor and dean of College of Sciences & Human Studies at Prince Mohammad Bin Fahd University. His research interests include analytical organic chemistry, environmental sustainability & assessment. He has published over 100 journal and conference proceedings papers and a book. Dr. Muhammad Ashraf has successfully carried out funded research projects related to these areas in relation to sustainable environment in the Kingdom of Saudi Arabia. Dr. Muhammad Ashraf is the recipient of research grants from prestigious funding agencies in the Kingdom. He has presented his research work at various renowned international conferences held in Europe, Canada, and USA. Dr. Muhammad Ashraf organized and chaired national and international conferences. He serves on a number of national and international professional committees. He is on editorial boards and a reviewer of a number of international journals. Dr. Ashraf is an active member of American Chemical Society (ACS), Association for the Advancement of Sustainability in Higher Education (AASHE), and Environmental Technology & Management Association (ETMA).Erscheint lt. Verlag | 12.7.2021 |
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Reihe/Serie | Computational Biology | Computational Biology |
Zusatzinfo | XIV, 369 p. 165 illus., 137 illus. in color. |
Sprache | englisch |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Mathematik / Informatik ► Mathematik | |
Naturwissenschaften ► Biologie | |
Schlagworte | Artificial Intelligence • Big Data • biochemistry • bio-inspired optimization • Biology • Biomaker Discovery • biomedicine • Chemistry • Computational Algorithms • Computational Intelligence • data analytics • Data Mining • Data Science • drug discovery • Fuzzy Logic • Knowledge Discovery • Life Science • machine learning • Medicine • Neural networks |
ISBN-10 | 3-030-69951-X / 303069951X |
ISBN-13 | 978-3-030-69951-2 / 9783030699512 |
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