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 Название: LLMs and Generative AI for Healthcare: The Next Frontier
Автор: Kerrie Holley, Manish Mathur
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 266
Язык: английский
Формат: epub
Размер: 43.0 MB
Large language models (LLMs) and Generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and Generative AI today and in the future, using storytelling and illustrative use cases in healthcare.
Authors Kerrie Holley, former Google healthcare professionals, guide you through the transformative potential of large language models (LLMs) and generative AI in healthcare. From personalized patient care and clinical decision support to drug discovery and public health applications, this comprehensive exploration covers real-world uses and future possibilities of LLMs and generative AI in healthcare.
With this book, you will:
Understand the promise and challenges of LLMs in healthcare
Learn the inner workings of LLMs and generative AI
Explore automation of healthcare use cases for improved operations and patient care using LLMs
Dive into patient experiences and clinical decision-making using generative AI
Review future applications in pharmaceutical R&D, public health, and genomics
Understand ethical considerations and responsible development of LLMs in healthcare
LLMs are natural language processing (NLP) machine learning models that can seemingly understand3 and generate human language text. LLMs are a type of artificial intelligence (AI) that comprehends and manipulates human language with remarkable proficiency. They are called “large” because they are trained on vast amounts of text data, often billions of words, which enables them to learn the nuances of human language.
For clinicians, LLMs can be thought of as advanced language processing tools that can assist with a variety of administrative tasks involving healthcare data (structured like electronic health records [EHRs] or unstructured doctor notes). Just as stethoscopes and X-ray machines extend a clinician’s abilities to assess a patient’s health, LLMs can enhance a clinician’s capacity to analyze and interpret large amounts of research data, email threads with embedded videos, a patient’s historical health records, clinical notes, discharge summaries, and more.
Generative AI is a subset or type of AI, just as LLMs and Machine Learning are types of AI. Generative AI is focused on creating new content such as text, images, video, or audio often in response to a user’s questions. The generated outputs often resemble human created content in terms of style and structure. When we use phrases such as LLMs or generative AI in this book, we do so as catch-all terms that encompass a wide range of AI systems, even if they have different attributes or employ different Machine Learning algorithms. These catch-all terms include but are not limited to LLMs, small language models, multimodal models, and generative AI.
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