This book provides an ideal foundation for readers to understand the application of artificial intelligence (AI) and machine learning (ML) techniques to expert systems in the healthcare sector. It starts with an introduction to the topic and presents chapters which progressively explain decision-making theory that helps solve problems which have multiple criteria that can affect the outcome of a decision. Key aspects of the subject such as machine learning in healthcare, prediction techniques, mathematical models and classification of healthcare problems are included along with chapters which delve in to advanced topics on data science (deep-learning, artificial neural networks, etc.) and practical examples (influenza epidemiology and retinoblastoma treatment analysis).
Key Features:
– Introduces readers to the basics of AI and ML in expert systems for healthcare
– Focuses on a problem solving approach to the topic
– Provides information on relevant decision-making theory and data science used in the healthcare industry
– Includes practical applications of AI and ML for advanced readers
– Includes bibliographic references for further reading
The reference is an accessible source of knowledge on multi-criteria decision-support systems in healthcare for medical consultants, healthcare policy makers, researchers in the field of medical biotechnology, oncology and pharmaceutical research and development.
The application gives a ranking result based on the selected criteria, their corresponding values and assigned weights. The book will also contain several practical applications of how decision-making theory could be used in solving problems related to selection of the best alternatives.
About the editor:
Dr Ilker Ozsahin have extensive experience in medical imaging devices such as PET and SPECT and been to University of Illinois at Urbana-Champaign, Illinois, the USA, to work on the growth of carbon nanotubes. He worked at Universidad Autonoma de Barcelona in Spain as a Ph.D. student for developing a PET scanner. He worked as a research assistant for six years in the Physics Department at Cukurova University in Adana, Turkey. Then, he worked at Harvard Medical School and Massachusetts General Hospital as a postdoctoral fellow. Also worked at the University of Macau as a visiting fellow for multi-pinhole brain and cardiac SPECT collimator design and implementation. Currently, as an Associate Professor in the Department of Biomedical Engineering at Near East University, He is working on the simulation of novel high-sensitivity and high-resolution PET and SPECT scanners, multi-criteria decision-making application on healthcare, as well as deep learning in medical imaging such as Alzheimer’s for high-accuracy classification and early detection.
Dr Dilber Uzun Ozsahin</…….