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:
This unique book, representing research from a team of international contributors, has not only real utility in academia for those in the medical and life sciences communities, but also a much wider readership from industry, science, and other areas of technology and education.
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
This unique book, representing research from a team of international contributors, has not only real utility in academia for those in the medical and life sciences communities, but also a much wider readership from industry, science, and other areas of technology and education.
Tuan D. Pham is professor and founding director of the Center for Artificial Intelligence at Prince Mohammad Bin Fahd University, Saudi Arabia.
Hong Yan is currently chair professor of computer engineering at City University of Hong Kong.
Dr. Muhammad Waqar Ashraf is professor and dean of College of Sciences & Human Studies at Prince Mohammad Bin Fahd University.
Folke Sjöberg is professor of burn surgery and critical care at Linköping University, Sweden, and director of the Burn Center at the Linköping University Hospital.
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"This book is a collection of articles on the application of artificial intelligence and machine learning methods in the field of medicine. ... The chapters on medical image analysis are
worthwhile reading, but of course this is also the kind of application where deep learning methods have become most successful. ... There is no doubt about the potential of AI to be used in medical applications ... ." (Florian Frommlet, SIAM Review, Vol. 65 (3), 2023)
worthwhile reading, but of course this is also the kind of application where deep learning methods have become most successful. ... There is no doubt about the potential of AI to be used in medical applications ... ." (Florian Frommlet, SIAM Review, Vol. 65 (3), 2023)