Data-Driven Decision Support System in Intelligent HealthCare (Hardcover)
Language: English
Published by Taylor & Francis Ltd, London, 2025
- Hardcover
- New
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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Hardcover. Machine Intelligence with Generative AI is one of the most trending topics with applications in almost all fields of life. In healthcare, it is not only accelerating the development of new products, but also automating the generation of new and synthetic content making it easier to train and improve machine learning models.Some of the biggest achievements of Generative AI in healthcare have been drug discovery, personalized care, differentially private synthetic data generation, operational efficiency, and many more. Generative AI models like Generative Adversarial Networks, and Variational Autoencoders are employed to generate synthetic medical images, aiding in data augmentation, facilitating disease diagnosis, and enabling advanced medical imaging research. Additionally, Generative AI techniques are being utilized for creating realistic electronic health records (EHRs) and simulated patient data, supporting privacy-preserving data sharing, and empowering innovative studies for personalized medicine and drug development. NLP models like ClinicalBERT use transformer-based deep learning architecture to understand and represent contextual information in large clinical text datasets, such as electronic health records (EHRs) and medical literature, and can better grasp medical terminologies, domain-specific language, and contextual nuances that are unique to the healthcare field.This volume delves into the realm of Machine Intelligence with Generative AI and explores its impact on the healthcare industry. Generative AI is one of the most trending topics and application in every field of Science and Engineering with AI and Machine Intelligence. It is used to develop new products and automate the system by generating the new and improved models and improve decision making systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9781032806273
- Title
- Data-Driven Decision Support System in Intelligent HealthCare (Hardcover)
- Author
- Debnath Bhattacharyya
- Publisher
- Taylor & Francis Ltd, London
- Publication year
- 2025
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1032806273
- ISBN 13
- 9781032806273
Machine Intelligence with Generative AI is one of the most trending topics with applications in almost all fields of life. In healthcare, it is not only accelerating the development of new products, but also automating the generation of new and synthetic content making it easier to train and improve machine learning models.
Some of the biggest achievements of Generative AI in healthcare have been drug discovery, personalized care, differentially private synthetic data generation, operational efficiency, and many more. Generative AI models like Generative Adversarial Networks, and Variational Autoencoders are employed to generate synthetic medical images, aiding in data augmentation, facilitating disease diagnosis, and enabling advanced medical imaging research. Additionally, Generative AI techniques are being utilized for creating realistic electronic health records (EHRs) and simulated patient data, supporting privacy-preserving data sharing, and empowering innovative studies for personalized medicine and drug development. NLP models like ClinicalBERT use transformer-based deep learning architecture to understand and represent contextual information in large clinical text datasets, such as electronic health records (EHRs) and medical literature, and can better grasp medical terminologies, domain-specific language, and contextual nuances that are unique to the healthcare field.
This volume delves into the realm of Machine Intelligence with Generative AI and explores its impact on the healthcare industry.
"Synopsis" may belong to another edition of this title.
About the Author
Debnath Bhattacharyya is a Professor in the Computer Science and Engineering Department, KL University, Bowrampet, Hyderabad, India. His research interests include Security Engineering, Pattern Recognition, Biometric Authentication, Multimodal Biometric Authentication, Data Mining and Image Processing.
Yu-Chen Hu is a Professor in the Department of Computer Science at Tunghai University, Taichung City, Taiwan. His interests include image and signal processing, data compression, information hiding, information security, computer network, deep learning, and data engineering.
"About the title" may belong to another edition of this title.
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