Application of generative AI in healthcare systems

Contributor(s):

Material type: Text

TextPublication details: Cham Springer 2025Description: xiii, 211 pISBN:

9783031829628

Subject(s):

Healthcare--AI

DDC classification:

610.285 ZAM

Summary: 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. (https://link.springer.com/book/10.1007/978-3-031-82963-5)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Public Policy & General Management	610.285 ZAM (Browse shelf(Opens below))	1	Available		009076

Table of contents:
Front Matter
Pages i-xiii
Download chapter PDF
Generative AI in Medical Imaging
Azadeh Tabatabaei, Armin ZadZiabari
Pages 1-33
Generative AI in Pandemic Prediction
Parisa Tavana, Mohammad ZareiNejad
Pages 35-66
Application of GenAI in Synthetic Data Generation in the Healthcare System
Amirfarhad Farhadi, Alireza Taheri
Pages 67-89
Application of GenAI in Clinical Administration Support
Alireza Taheri, Amirfarhad Farhadi, Azadeh Zamanifar
Pages 91-117
Application of Generative AI in Patient Engagement
Mohammad ZareiNejad, Parisa Tavana
Pages 119-154
Application of Generative AI in Drug Discovery
Amirfarhad Farhadi, Azadeh Zamanifar, Miad Faezipour
Pages 155-174
Application of Generative AI in Resource Optimization in Healthcare Systems
Homayoun Safarpour Motealegh Mahalegi, Amirfarhad Farhadi, Gergő Balogh, Eniko Nagy
Pages 175-195
Ethics and Regulations in Generative AI
Armin ZadZiabari, Azadeh Tabatabaei
Pages 197-211

[https://link.springer.com/book/10.1007/978-3-031-82963-5]

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.

(https://link.springer.com/book/10.1007/978-3-031-82963-5)

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