Generative AI in Modern Healthcare brings together research and practical insights on how technologies like machine learning, deep learning, generative AI, and federated learning are transforming healthcare. It explains how these tools are improving diagnosis, treatment planning, and patient care.

The book covers key areas such as personalised medicine, predictive analytics, telemedicine, and AI-based healthcare systems. It also highlights the growing role of AI in medical imaging and diagnostics across fields like radiology, pathology, and cardiology.

In addition, the book explores how AI supports drug discovery, disease prediction, and clinical decision-making, using real-world examples and datasets. It also discusses key challenges, including data quality, bias, privacy, and ethical concerns, as well as secure approaches such as federated learning.

Overall, the book provides a clear understanding of how AI is shaping modern healthcare and improving outcomes.

Key Features

Covers major AI applications in healthcare, including diagnosis and patient care

Explains machine learning, deep learning, and generative AI in simple terms

Includes real-world examples and case studies

Highlights AI use in drug discovery and personalised medicine

Discusses ethics, privacy, and data challenges

Introduces emerging tools like federated learning and large language models

Target Readership

Researchers, academics, students, and professionals in AI, data science, healthcare, and biomedical fields.