Analytics is now an integral part of healthcare. It helps to optimize treatments, improve outcomes, and the reduce the overall cost of care. The availability of biomedical, healthcare, and operational big data enables hospitals and health systems to leverage past data to predict the future of patients and their clinical pathways. Predictive modeling and healthcare data science also help to design care pathways and operational strategies that could help in streamlining various aspects of healthcare delivery. However, healthcare analytics is an exciting field that requires skills in biomedicine, data science, and the technical stack, including databases, programming, data visualization, statistics, and machine learning. While there are several books with an in-depth account of the healthcare space and analytics tools and methods, there not many easy-to-read books that integrate these things together.
In his new and exciting book, Dr. Vikas Kumar (Vik) has now blended the critical learning points of healthcare and computer science with mathematics and machine learning. Being a physician and a data scientist, Vik has done a tremendous job in compiling complex datasets and explaining several use cases in healthcare analytics with comprehensive code in MySQL and Python.
I am sure that Healthcare Analytics Made Simple will be an important addition to the library of any data scientist who's interested in understanding the key concepts of biomedical and healthcare data. It will be an indispensable companion for readers from the domains of clinical informatics and health informatics to gain critical skills in the design, development, and validation of machine learning models. This book will also be useful for physicians and biomedical scientists who are interested in understanding the landscape of healthcare analytics. The book is a joy to read, and I enjoyed working through the examples. To conclude, Healthcare Analytics Made Simple is attempting to fill a gap in the field of healthcare analytics by providing a complete and comprehensive guide, resulting in an inter-disciplinary book that will be an easy read for computer scientists, software engineers, data scientists, and healthcare professionals alike.
Dr. Shameer Khader, PhD
Director of Healthcare Data Science and Bioinformatics
Northwell Health, New York