Hands-On Healthcare Data: Taming the Complexity of Real-World Data

Healthcare is the next frontier for data science, and this book provides pragmatic and hands-on solutions for working with healthcare data. It covers specific ML and deep learning examples with a focus on producing high-quality data and how graph technologies help connect disparate data sources.

Format: Paperback / softback
Length: 250 pages
Publication date: 23 August 2022
Publisher: O'Reilly Media

The field of healthcare is poised to undergo a remarkable transformation through the application of data science. By harnessing the latest advancements in machine learning, deep learning, and natural language processing, healthcare professionals will be able to address some of the most pressing challenges facing the industry. These include reducing the cost of care, ensuring optimal treatment for patients, and increasing accessibility for underserved populations.

To navigate this complex landscape, this book offers practical and hands-on solutions for working with healthcare data. It begins by exploring the various types of healthcare data, including electronic health records, clinical registries, digital health tools, and claims data. The authors then delve into the challenges of working with healthcare data, particularly when attempting to aggregate data from multiple sources. They discuss current options for extracting structured data from clinical text and highlight the importance of making trade-offs when utilizing tools and frameworks for normalizing structured healthcare data.

Furthermore, the book explores how to harmonize healthcare data using terminologies, ontologies, and mappings and crosswalks. It emphasizes the significance of standardizing data formats and terminology to facilitate data exchange and integration across different healthcare systems. By leveraging graph technologies, the authors demonstrate how disparate data sources can be connected to solve healthcare's most challenging problems using advanced analytics.

Throughout the book, real-world examples and case studies are provided to illustrate the practical applications of data science in healthcare. The authors use a step-by-step approach to guide readers through the process of extracting, cleaning, and analyzing healthcare data, enabling them to make informed decisions and drive positive outcomes.

Whether you are a healthcare professional, researcher, or data analyst, this book provides valuable insights and techniques for working with healthcare data. It serves as a comprehensive guide that will help you unlock the full potential of data science in healthcare and contribute to the improvement of patient care and health outcomes.

Dimension: 232 x 178 (mm)
ISBN-13: 9781098112929