Healthcare Analytics Made Simple

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Dan Clark
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Sponsored Post.By Vikas (Vik) Kumar

Together, we’ll use data science, machine learning, and analytics to improve healthcare outcomes.

Highlights of the book include:

  • Set up the toolbox:Set up the Anaconda distribution of Python as well as Jupyter notebook and SQLite with step-by-step instructions (Chapter 1).

  • Caring about healthcare:An A to Z primer on healthcare including topics such as financing, policy, HIPAA, clinical coding systems, and how clinical data travels from the patient to the computer (Chapter 2).

  • Thinking like the physician:Learn how physicians are trained to approach clinical cases and how this relates to machine learning algorithms such as decision trees, logistic regression, and neural networks (Chapter 3).

  • Set the clinical table:Learn SQL by example and use it to munge a mini clinical database of cardiology patients (Chapter 4).

  • Don’t mind the Python:A tutorial on the Python programming language (Chapter 5), including syntax, data types and containers, and scripts.

  • Getting friendly with pandas:Learn how to wrangle data quickly and easily using the popular pandas library (Chapter 5).

  • Caring about quality: See how governmental incentive programs are creating opportunities for providers to get reimbursed financially (Chapter 6).

  • Emergency Department modeling:Join us as we build a predictive model in Python from start to finish, from downloading the data to measuring model performance (Chapter 7).

  • Real-world modeling:Read how recent machine learning studies are redefining clinical practice and knowledge in the areas of heart disease, cancer, and readmission prediction (Chapter 8).

  • The chosen future:Discuss the most recent advances in healthcare analytics and discuss barriers to adoption (Chapter 9).

All in all, Healthcare Analytics Made Simple is a valuable resource for any data scientist interested in healthcare.  Buy your copy today at Amazon or Packtpub.com.

Bio: Vikas (Vik) Kumar grew up in the United States in Upstate New York. He earned his MD from the University of Pittsburgh but shortly after that, he discovered his true calling of computers and data science. He then completed MS in the College of Computing at Georgia Institute of Technology. He currently lives in Atlanta, Georgia and works as a data scientist.