Healthcare: EBooks

Over the past 50 years, scientists have made incredible progress in the application of genetic research to human health care and disease treatment. Innovative tools and techniques, including gene therapy and CRISPR-Cas9 editing, can treat inherited disorders that were previously untreatable, or prevent them from happening in the first place. You can take a DNA test to learn where your ancestors are from. Police officers can use genetic evidence to identify criminals--or innocents. And some doctors are using new medical techniques for unprecedented procedures. Genomics: A Revolution in Health and Disease Discovery delves into the history, science, and ethics behind recent breakthroughs in genetic research. Authors Whitney Stewart and Hans Andersson, MD, present fascinating case studies that show how real people have benefitted from genetic research. Though the genome remains full of mysteries, researchers and doctors are working hard to uncover its secrets and find the best ways to treat patients and cure diseases. The discoveries to come will inform how we target disease treatment, how we understand our health, and how we define our very identities.

Despite being the wealthiest nation on earth, the United States spends much of its healthcare money and resources pursuing the wrong goal: curing people after they get sick. In this provocative book, Nicholas J. Webb charts a bold new path that puts the focus not on reactionary treatment but on anticipation and prevention. Webb argues that we have a unique opportunity to leverage disruptive innovation to fulfill these goals. Emerging digital technologies now make it possible to collect, analyze, and act upon the enormous quantities of health-related data that every individual generates every day.

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. But first, you have to 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 harmonization 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. You'll learn: 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