"In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists' work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples"--
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Dr. Vikas (Vik) Kumar grew up in the United States in Niskayuna, New York. He earnedhis MD from the University of Pittsburgh, but shortly afterwards he discovered his truecalling of computers and data science. He then earned his MS in the College of Computingat Georgia Institute of Technology and has subsequently worked as a data scientist for bothhealthcare and non-healthcare companies. He currently lives in Atlanta, Georgia.
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Paperback. Condición: New. Machine learning and analytics have been widely utilized across the healthcare sector of late. This book will bridge the gap between practicing doctors and you as a data scientist. You will learn how to work with healthcare data and gain better insight from this data to improve healthcare outcomes. Nº de ref. del artículo: LU-9781787286702
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