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Artificial Intelligence in Healthcare = Recent Applications and Developments /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Artificial Intelligence in Healthcare/ edited by Tianhua Chen, Jenny Carter, Mufti Mahmud, Arjab Singh Khuman.
Reminder of title:
Recent Applications and Developments /
other author:
Chen, Tianhua.
Description:
VIII, 227 p. 127 illus., 106 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Medical informatics. -
Online resource:
https://doi.org/10.1007/978-981-19-5272-2
ISBN:
9789811952722
Artificial Intelligence in Healthcare = Recent Applications and Developments /
Artificial Intelligence in Healthcare
Recent Applications and Developments /[electronic resource] :edited by Tianhua Chen, Jenny Carter, Mufti Mahmud, Arjab Singh Khuman. - 1st ed. 2022. - VIII, 227 p. 127 illus., 106 illus. in color.online resource. - Brain Informatics and Health,2367-1750. - Brain Informatics and Health,.
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 healthcare service 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.
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, early career 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.
ISBN: 9789811952722
Standard No.: 10.1007/978-981-19-5272-2doiSubjects--Topical Terms:
583858
Medical informatics.
LC Class. No.: R858-859.7
Dewey Class. No.: 610.285
Artificial Intelligence in Healthcare = Recent Applications and Developments /
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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 healthcare service 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.
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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, early career 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.
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