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Generative AI

Written by Rohit Mahajan,Ritu M. Uberoy

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198 pages, about 4 hours of reading

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About this book

From algorithms that draft clinical notes in seconds to autonomous agents that triage emergency room backlogs, artificial intelligence is quietly reshaping every facet of healthcare. Generative AI: Unlocking the Next Chapter in Healthcare is the first comprehensive guide to this revolution—charting how we got here, what’s working now, and where the technology could take us next. Drawing on frontline case studies from leading health systems, biotech labs, and tech giants, the book reveals how large language models, synthetic data engines, and multi agent ecosystems are boosting diagnostic accuracy, accelerating drug discovery, and personalizing patient engagement. It also confronts the hard questions—privacy, bias, liability, and the fear of “machines taking over”—offering clear, actionable frameworks for ethical, human centered deployment. Written for clinicians, executives, innovators, and policy makers and patients alike, this definitive volume distils the expertise of industry pioneers into an accessible roadmap. You’ll explore: • The evolution from early machine learning to today’s generative powerhouses • Real world wins—ambient documentation, AI assisted radiology, virtual nursing, and more • The players shaping the landscape: Epic, Google, Microsoft, NVIDIA, Salesforce, and a wave of insurgent startups • Guardrails that preserve trust, protect privacy, and keep humans in the loop • Bold yet plausible futures—from digital twin medicine to globe-spanning agent networks Whether you’re leading a hospital, building health tech solutions, a tech startup, or simply curious about the future of care, Generative AI: Unlocking the Next Chapter in Healthcare delivers the insight, inspiration, and practical guidance you need to thrive in the era where human empathy and machine intelligence work side by side.

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Reading guide

Themes, characters and key ideas in Generative AI, written by Chaptra AI.

  • about 20 hours
  • intermediate
  • informative
  • technical
  • instructive

This comprehensive technical guide, "Generative AI" by Rohit Mahajan and Ritu M. Uberoy, meticulously unpacks the complex landscape of artificial intelligence models capable of creating new data. The book systematically progresses from foundational concepts of machine learning and neural networks to advanced architectures like GANs, VAEs, Large Language Models (LLMs), and diffusion models. It provides a structured understanding of how these technologies work, their diverse applications across various domains, and critically examines the ethical considerations and societal impacts inherent in their development and deployment. Aimed at a broad audience from students to practitioners, it serves as an essential resource for navigating the rapidly evolving field of generative AI.

Generative AI models are capable of creating novel data instances that resemble the training data, rather than just classifying or predicting.

Key themes

Core Generative Models and Architectures
Central to the book, this theme delves into the specifics of key generative models such as GANs, VAEs, LLMs (Transformers), and Diffusion Models. It explains their internal mechanisms, training processes, and distinct capabilities.
Applications and Impact of Generative AI
This theme examines the diverse real-world applications of generative AI across various domains, showcasing its transformative potential and impact on industries and daily life. It highlights how these models are being used to solve complex problems and create new possibilities.
Foundations of Generative AI
This theme explores the underlying machine learning, deep learning, and neural network principles that serve as prerequisites for understanding generative models. It establishes the theoretical bedrock upon which more complex architectures are built.

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What are the most significant ethical challenges posed by the proliferation of generative AI, and how can they be mitigated?

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