Introduction to Biomedical Data Science

Data science has steadily increased in popularity over the past decade and involves all industries, including healthcare and the biomedical sciences. The goal in healthcare is to use data science methods to improve medical quality and safety and reduce costs.

There is optimism that machine learning and artificial intelligence (AI) will be major drivers of predictive analytics, image, voice, and text recognition. Recently, applied AI models have outperformed medical experts at classifying medical images—particularly in cardiology, dermatology, ophthalmology, and radiology.

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This textbook (2019) was written for anyone in the medical or informatics fields who feels they need a stronger background in data science. Understanding the textbook content and data exercises does not require programming skills or higher math. Chapter exercises are based on healthcare data, and supplemental YouTube videos are available in most chapters. The content begins with spreadsheet tips and tricks and ends with artificial intelligence.

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Table of Contents

Chapter 1: Overview of Biomedical Data Science

Chapter 2: Spreadsheet Tips and Tricks

Chapter 3: Biostatistics Primer

Chapter 4: Data Visualization

Chapter 5: Introduction to Databases

Chapter 6: Big Data

Chapter 7: Bioinformatics and Precision Medicine

Chapter 8: Programming Languages

Chapter 9: Artificial Intelligence and Medicine

Chapter 10: Biomedical Data Science Resources