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Artificial Intelligence and Machine Learning for Healthcare : Vol. 2: Emerging Methodologies and Trends / edited by Chee Peng Lim, Ashlesha Vaidya, Yen-Wei Chen, Vaishnavi Jain, Lakhmi C. Jain.
- Format:
- Book
- Series:
- Intelligent Systems Reference Library, 1868-4408 ; 229
- Language:
- English
- Subjects (All):
- Medical informatics.
- Artificial intelligence.
- Health Informatics.
- Artificial Intelligence.
- Local Subjects:
- Health Informatics.
- Artificial Intelligence.
- Physical Description:
- 1 online resource (282 pages)
- Edition:
- 1st ed. 2023.
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2023.
- Summary:
- In line with advances in digital and computing systems, artificial intelligence (AI) and machine learning (ML) technologies have transformed many aspects of medical and healthcare services, delivering tangible benefits to patents and the general public. This book is a sequel of the edition on “Artificial Intelligence and Machine Learning for Healthcare”. The first volume is focused on utilization of AI and ML for image and data analytics in the medical and healthcare domains. In this second volume, emerging methodologies and future trends in AI and ML for advancing medical treatments and healthcare services are presented. The selected studies in this book provide readers a glimpse on current progresses in AI and ML for undertaking a variety of healthcare-related tasks. The advances in AI and ML technologies for future healthcare are also discussed, shedding light on the potential of AI and ML to realize the next-generation medical treatments and healthcare services for the betterment of our global society.
- Contents:
- Artificial Intelligence for the future of medicine
- A Survival Analysis Guide in Oncology
- Social Media Sentiment Analysis related to COVID-19 Vaccinations
- Healthcare support using data mining: A case study on stroke prediction. .
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-031-11170-2
- OCLC:
- 1348484730
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