Hands-On Healthcare Data: Taming the Complexity of Real-World Data (Paperback)
暫譯: 實作醫療數據：駕馭現實世界數據的複雜性 (平裝本)
Nguyen, Andrew
- 出版商: O'Reilly
- 出版日期: 2022-09-20
- 定價: $2,800
- 售價: 8.8 折 $2,464 (限時優惠至 2025-03-31)
- 語言: 英文
- 頁數: 242
- 裝訂: Quality Paper - also called trade paper
- ISBN: 109811292X
- ISBN-13: 9781098112929
-
相關分類:
Data Science
立即出貨 (庫存 < 3)
買這商品的人也買了...
-
生物統計學(概要)歷屆試題詳解, 2/e (106～92年)(適用: 高普考．地方政府特考．各類特考．升等升資)$480$432 -
圖解！大數據下必學的統計基礎$350$298 -
New Advances in Statistics and Data Science (ICSA Book Series in Statistics)$3,500$3,325 -
Deep learning 深度學習必讀 - Keras 大神帶你用 Python 實作 (Deep Learning with Python)$1,000$790 -
Data Science from Scratch｜用 Python 學資料科學, 2/e (中文版)(Data Science from Scratch: First Principles with Python, 2/e)$680$537 -
AIOT 與 OpenCV 實戰應用：Python、樹莓派、物聯網與機器視覺$480$379 -
機器學習設計模式 (Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and Mlops)$680$537 -
資料科學家的實用統計學 : 運用 R 和 Python 學習 50+個必學統計概念, 2/e (Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, 2/e)$680$537 -
$1,848How to Lead in Data Science -
AI 開發的機器學習系統設計模式$620$490 -
Python 統計分析：生命科學應用 (An Introduction to Statistics with Python: With Applications in the Life Sciences)$500$375 -
圖解統計與大數據, 3/e$350$315
商品描述
Healthcare is the next frontier for data science. Using the latest in machine learning, deep learning, and natural language processing, you'll be able to solve healthcare's most pressing problems: reducing cost of care, ensuring patients get the best treatment, and increasing accessibility for the underserved-once you learn how to access and make sense of all that data.
This book provides pragmatic and hands-on solutions for working with healthcare data, from data extraction to cleaning and normalizing to feature engineering. Author Andrew Nguyen covers specific ML and deep learning examples with a focus on producing high-quality data. You'll discover how graph technologies help you connect disparate data sources so you can solve healthcare's most challenging problems using advanced analytics.
With this book, you'll learn:
- The different types of healthcare data: electronic health records, clinical registries and trials, digital health tools, and claims data
- The challenges of working with healthcare data, especially when trying to aggregate data from multiple sources
- Current options for extracting structured data from clinical text
- How to make trade-offs when using tools and frameworks for normalizing structured healthcare data
- How to harmonize healthcare data using terminologies, ontologies, and mappings and crosswalks
商品描述(中文翻譯)
醫療保健是數據科學的下一個前沿。利用最新的機器學習、深度學習和自然語言處理技術，您將能夠解決醫療保健中最迫切的問題：降低護理成本、確保患者獲得最佳治療，以及提高弱勢群體的可及性——一旦您學會如何訪問和理解所有這些數據。
本書提供了針對醫療數據的務實和實用解決方案，涵蓋從數據提取到清理、標準化再到特徵工程的各個方面。作者 Andrew Nguyen 涵蓋了具體的機器學習和深度學習範例，重點在於產生高質量的數據。您將發現圖形技術如何幫助您連接不同的數據來源，以便利用先進的分析技術解決醫療保健中最具挑戰性的問題。
通過本書，您將學到：
- 醫療數據的不同類型：電子健康紀錄、臨床登記和試驗、數位健康工具以及索賠數據
- 處理醫療數據的挑戰，特別是在嘗試從多個來源聚合數據時
- 從臨床文本中提取結構化數據的當前選項
- 在使用工具和框架標準化結構化醫療數據時如何進行取捨
- 如何使用術語、範疇、映射和交叉走道來協調醫療數據
作者簡介
Andrew Nguyen has been working at the intersection of healthcare data and machine learning for over a decade. He quickly discovered graph databases and has been using them to harmonize disparate data sources for nearly as long. Andrew holds a PhD in Biological and Medical Informatics from UCSF and a BS in Electrical and Computer Engineering from UCSD. He has worked for a variety of organizations, from academia to startups. He is currently a Principal Medical Informatics Architect at one of the largest biopharma companies in the world, where he is designing scalable solutions to harmonize healthcare real world data sources for machine learning and advanced analytics.
作者簡介(中文翻譯)
安德魯·阮（Andrew Nguyen）在醫療數據與機器學習的交匯處工作了十多年。他很快發現了圖形資料庫，並幾乎同樣長的時間以來一直在使用它們來協調不同的數據來源。安德魯擁有加州大學舊金山分校（UCSF）生物醫學資訊學的博士學位，以及加州大學聖地牙哥分校（UCSD）電機與計算機工程的學士學位。他曾在各種組織工作，從學術界到初創公司。目前，他是全球最大的生物製藥公司之一的首席醫療資訊架構師，負責設計可擴展的解決方案，以協調醫療現實世界數據來源，供機器學習和高級分析使用。
