LLM and Generative AI for Healthcare: A Comprehensive Guide

Vemula, Anand, Vemula

  • 出版商: Independently Published
  • 出版日期: 2024-07-15
  • 售價: $1,030
  • 貴賓價: 9.5$979
  • 語言: 英文
  • 頁數: 34
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798333169464
  • ISBN-13: 9798333169464
  • 相關分類: LangChain人工智慧
  • 海外代購書籍(需單獨結帳)

買這商品的人也買了...

商品描述

"LLM and Generative AI for Healthcare: A Comprehensive Guide" explores the transformative power of Large Language Models (LLMs) and Generative AI in the healthcare industry. This book provides a deep dive into how these cutting-edge technologies are revolutionizing medical practices, enhancing patient care, and optimizing operational efficiency.

The journey begins with an introduction to LLMs and Generative AI, offering a clear understanding of their evolution, capabilities, and significance in healthcare. It delves into the fundamentals of healthcare data, emphasizing the types of data, privacy, security considerations, and regulatory compliance, which are crucial for any AI application in this sector.

In the second part, the book showcases various applications of AI in healthcare. It covers AI's role in medical imaging and diagnostics, highlighting advancements in radiology and automated image analysis through real-world case studies. The book also explores Natural Language Processing (NLP) applications, including clinical documentation, EHR management, voice assistants, and text mining for research and drug discovery. Furthermore, it discusses personalized medicine, predictive analytics for patient outcomes, and AI's role in drug discovery and development.

The third part focuses on the implementation of AI solutions in healthcare. It provides practical guidance on designing AI systems, integrating them with existing healthcare infrastructure, and key design considerations. The book also covers data management, preprocessing techniques, and ensuring data quality, followed by model training, evaluation, deployment strategies, and continuous improvement.

Real-world case studies and lessons learned from successful AI implementations are presented in the fourth part. This section also addresses the ethical and legal considerations of AI in healthcare, emphasizing the importance of fairness, transparency, and compliance with regulations. The book concludes with a look at future trends and innovations in AI, preparing readers for upcoming technological advancements.

The final part offers hands-on tutorials and exercises, guiding readers through the setup and use of popular AI tools and libraries. It includes basic and advanced projects, such as building medical chatbots and diagnostic tools, to reinforce learning and practical application.

"LLM and Generative AI for Healthcare: A Comprehensive Guide" is an essential resource for healthcare professionals, data scientists, and AI enthusiasts looking to harness the power of AI to improve healthcare outcomes.

商品描述(中文翻譯)

《LLM 和生成式 AI 在醫療保健中的應用:全面指南》探討了大型語言模型(LLMs)和生成式 AI 在醫療行業的變革力量。本書深入分析了這些尖端技術如何徹底改變醫療實踐、提升病人護理和優化運營效率。

本書的旅程始於對 LLMs 和生成式 AI 的介紹,提供了對其演變、能力和在醫療保健中重要性的清晰理解。它深入探討了醫療數據的基本原則,強調數據類型、隱私、安全考量和法規遵循,這些對於該領域的任何 AI 應用都是至關重要的。

在第二部分中,本書展示了 AI 在醫療保健中的各種應用。它涵蓋了 AI 在醫學影像和診斷中的角色,通過真實案例研究突顯放射學和自動影像分析的進展。本書還探討了自然語言處理(NLP)應用,包括臨床文檔、電子健康紀錄(EHR)管理、語音助手和用於研究及藥物發現的文本挖掘。此外,它還討論了個性化醫療、預測分析對病人結果的影響,以及 AI 在藥物發現和開發中的角色。

第三部分專注於 AI 解決方案在醫療保健中的實施。它提供了設計 AI 系統、將其與現有醫療基礎設施整合的實用指導,以及關鍵設計考量。本書還涵蓋了數據管理、預處理技術和確保數據質量,隨後是模型訓練、評估、部署策略和持續改進。

第四部分呈現了成功 AI 實施的真實案例研究和經驗教訓。本節還討論了 AI 在醫療保健中的倫理和法律考量,強調公平性、透明度和遵守法規的重要性。本書最後展望了 AI 的未來趨勢和創新,為讀者準備即將到來的技術進步。

最後一部分提供了實用的教程和練習,指導讀者設置和使用流行的 AI 工具和庫。它包括基本和進階項目,例如構建醫療聊天機器人和診斷工具,以加強學習和實際應用。

《LLM 和生成式 AI 在醫療保健中的應用:全面指南》是醫療專業人士、數據科學家和 AI 愛好者的重要資源,旨在利用 AI 的力量改善醫療結果。