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Application of generative AI in healthcare systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Application of generative AI in healthcare systems/ edited by Azadeh Zamanifar, Miad Faezipour.
other author:	Zamanifar, Azadeh.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xiii, 211 p. :ill., digital ;24 cm.
[NT 15003449]:	Generative AI in Medical Imaging -- Generative AI in Pandemic Prediction -- Application of GenAI in Synthetic Data Generation in the healthcare system -- Application of GenAI in Clinical Administration Support -- Application of Generative AI in Patient Engagement -- Application of Generative AI in Drug discovery -- Application of Generative AI in Resource Optimization in Healthcare Systems -- Ethics and Regulations in Generative AI.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence - Medical applications. -
Online resource:	https://doi.org/10.1007/978-3-031-82963-5
ISBN:	9783031829635

Application of generative AI in healthcare systems
Application of generative AI in healthcare systems[electronic resource] /edited by Azadeh Zamanifar, Miad Faezipour. - Cham :Springer Nature Switzerland :2025. - xiii, 211 p. :ill., digital ;24 cm.

Generative AI in Medical Imaging -- Generative AI in Pandemic Prediction -- Application of GenAI in Synthetic Data Generation in the healthcare system -- Application of GenAI in Clinical Administration Support -- Application of Generative AI in Patient Engagement -- Application of Generative AI in Drug discovery -- Application of Generative AI in Resource Optimization in Healthcare Systems -- Ethics and Regulations in Generative AI.

Generative AI has immensely influenced various fields, such as education, marketing, art and music, and especially healthcare. Generative AI can benefit the patient through various approaches. For instance, it can enhance the image qualities negatively affected by radiation reduction, preventing patients from needing to repeat the image-taking process. Also, the generation of one type of image from another more expensive one can help patients save funds. Generative AI facilitates the administrative process, letting the doctor focus more on the treatment process. It even goes further by helping medical professionals with diagnosis and decision- making, suggesting possible treatment plans according to the patient symptoms. This book introduces several practical GenAI healthcare applications, especially in medical imaging, pandemic prediction, synthetic data generation, clinical administration support, professional education, patient engagement, and clinical decision support, providing a review of efficient GenAI tools and frameworks in this area. GenAI empowers the treatment process through several methods; however, some ethical, privacy, and security challenges require attention. Despite the challenges presented, GenAI technological and inherited characteristics smooth the path of improvement for it in the future.

ISBN: 9783031829635

Standard No.: 10.1007/978-3-031-82963-5doiSubjects--Topical Terms:

900591
Artificial intelligence
--Medical applications.

LC Class. No.: R859.7.A78

Dewey Class. No.: 610.28563

Application of generative AI in healthcare systems
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520 $a Generative AI has immensely influenced various fields, such as education, marketing, art and music, and especially healthcare. Generative AI can benefit the patient through various approaches. For instance, it can enhance the image qualities negatively affected by radiation reduction, preventing patients from needing to repeat the image-taking process. Also, the generation of one type of image from another more expensive one can help patients save funds. Generative AI facilitates the administrative process, letting the doctor focus more on the treatment process. It even goes further by helping medical professionals with diagnosis and decision- making, suggesting possible treatment plans according to the patient symptoms. This book introduces several practical GenAI healthcare applications, especially in medical imaging, pandemic prediction, synthetic data generation, clinical administration support, professional education, patient engagement, and clinical decision support, providing a review of efficient GenAI tools and frameworks in this area. GenAI empowers the treatment process through several methods; however, some ethical, privacy, and security challenges require attention. Despite the challenges presented, GenAI technological and inherited characteristics smooth the path of improvement for it in the future.
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