Artificial Intelligence in Healthcare, 1st ed. 2022 Recent Applications and Developments Brain Informatics and Health Series
Langue : Anglais
Recent advances in artificial intelligence (AI) and machine learning have witnessed many successes in various disciplines including the healthcare sector. Innovations in intelligent medical systems have revolutionized the way in which healthcare services are provided, ranging from making clinical diagnosis, developing personalized treatment and drugs, assisting patient monitoring, to automating administrative tasks and reducing operational costs. In this book, the authors present key applications in the general area of health care, where AI has made significant successes.
From the individual chapters, the readers will be provided with a range of examples to illustrate the wide plethora of application domains utilizing state-of-the-art AI techniques, proving credence to the versatility and effectiveness of an AI approach in health care and medicine. We envisage that this book is ideal for individuals new to the notion of AI in health care, equally, earlycareer academics who wish to further expand on their knowledge in AI in medicine. What will be presented is in no means an exhaustive list of applications, but most definitely a varied one.
Chapter 1. Deep fuzzy neural network in dementia.- Chapter 2. Machine learning for COVID detection.- Chapter 3. Machine Learning techniques applied to identify significant gene biomarkers for efficient cancer treatment.- Chapter 4. Group decision making in intelligent medicine.- Chapter 5. Fuzzy logic system for diabetic eye detection.- Chapter 6. Sentiment analysis using deep neural networks.- Chapter 7. The emerging role of AI in dementia research and healthcare.- Chapter 8. Identifying high impact underlying conditions in disease management using AI.- Chapter 9. AI in medicine- case in Asthma diagnosis.- Chapter 10. Sentiment Analysis of Stroke Tweet.- Chapter 11. Artificial intelligence in detecting Alzheimer’s Disease.- Chapter 12. Intelligent systems for IoT based healthcare delivery.- Chapter 13. Machine learning for the detection of Schizophrenia.- Chapter 14. Ictal discharge detection from neuronal signals using machine learning.- Chapter 15. Sentiment analysis for healthcareservice provisioning.- Chapter 16. AI Healthcare: Malignant or Benign.- Chapter 17. Machine learning for dementia diagnosis.- Chapter 18. Using fuzzy systems to calculate blood pressure levels.
Dr. Tianhua Chen received the Ph.D. degree in Computer Science in 2017 from Aberystwyth University, Aberystwyth, UK. He is currently Senior Lecturer in Artificial Intelligence with the Department of Computer Science, School of Computing and Engineering, University of Huddersfield, Huddersfield, UK. With research supported by Research England, NHS among various stakeholders, Dr. Chen has published over 50 peer-reviewed papers in leading international journals and conferences. While sitting in the Editorial Board of Artificial Intelligence in Medicine journal, he is very keen translating AI techniques in the healthcare sector, particularly mental health. He has also previously edited a book volume and numerous special issues in journals such as Artificial Intelligence in Medicine and Frontiers in Neuroscience.
Dr. Jenny Carter gained a Ph.D. in Artificial Intelligence Techniques and Musical Style Analysis in 2004. She is now semi-retired and works ona part-time basis at Huddersfield University. She is former Subject Area Leader in Computing & Information Systems at Huddersfield University. Prior to October 2017, she was Associate Head of School of Computer Science & Informatics at De Montfort University and Subject Group Leader for Computer Science & Security. She was also Faculty Academic Development Partner. Her teaching expertise includes fuzzy logic, data mining, knowledge-based systems, and databases. Her specialist areas for research are e-learning in higher education and applications of AI, in particular to music-related problems. She has a number of journal and conference publications as well as 3 previous edited books.
Dr Mufti Mahmud is an Associate Professor of Cognitive Computing at the Computer Science Department of Nottingham Trent University (NTU), UK. He has been the recipient of the top 2% cited scientists worldwide in computer science (2020), the NTU VC outstanding research award
Broadens your understanding of artificial intelligence in enhancing clinical practice and delivery Covers many different applications of AI-powered health systems Includes case studies that illustrate how artificial intelligence can be incorporated into healthcare systems
Date de parution : 10-2023
Ouvrage de 227 p.
15.5x23.5 cm
Date de parution : 10-2022
Ouvrage de 227 p.
15.5x23.5 cm
Thèmes d’Artificial Intelligence in Healthcare :
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