Healthcare Analytics Made Simple

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Healthcare Analytics Made Simple

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Một cuốn sách cực hay viết về machine learning trong ngành y. Sách viết đơn giản, sử dụng các ví dụ về machine learning trong y khoa với Python. Sách gồm chín chương đề cập đến các vấn đề liên quan đến machine learning trong y khoa như healthcare quality, predictive model. Sách viết đơn giản dễ hiểu rất cần thiết cho người muốn học meachine learning với Python trong ngành y

Healthcare Analytics Made Simple Techniques in healthcare computing using machine learning and Python Vikas (Vik) Kumar BIRMINGHAM - MUMBAI Healthcare Analytics Made Simple Copyright © 2018 Packt Publishing All rights reserved No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews Every effort has been made in the preparation of this book to ensure the accuracy of the information presented However, the information contained in this book is sold without warranty, either express or implied Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals However, Packt Publishing cannot guarantee the accuracy of this information Commissioning Editor: Veena Pagare Acquisition Editor: Divya Poojari Content Development Editor: Eisha Dsouza Technical Editor: Sneha Hanchate Copy Editor: Safis Project Coordinator: Namrata Swetta Proofreader: Safis Editing Indexer: Rekha Nair Graphics: Jisha Chirayil Production Coordinator: Shantanu Zagade First published: July 2018 Production reference: 1280718 Published by Packt Publishing Ltd Livery Place 35 Livery Street Birmingham B3 2PB, UK ISBN 978-1-78728-670-2 www.packtpub.com To my parents, Viren and Sarita; my sister, Monica; and Tuly, my 2018 Person of the Year mapt.io Mapt is an online digital library that gives you full access to over 5,000 books and videos, as well as industry leading tools to help you plan your personal development and advance your career For more information, please visit our website Why subscribe? Spend less time learning and more time coding with practical eBooks and Videos from over 4,000 industry professionals Improve your learning with Skill Plans built especially for you Get a free eBook or video every month Mapt is fully searchable Copy and paste, print, and bookmark content PacktPub.com Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at www.PacktPub.com and as a print book customer, you are entitled to a discount on the eBook copy Get in touch with us at service@packtpub.com for more details At www.PacktPub.com, you can also read a collection of free technical articles, sign up for a range of free newsletters, and receive exclusive discounts and offers on Packt books and eBooks Foreword 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 Contributors ... Introduction to Healthcare Analytics What is healthcare analytics? Healthcare analytics uses advanced computing technology Healthcare analytics acts on the healthcare industry (DUH!) Healthcare analytics improves medical care.. .Healthcare Analytics Made Simple Techniques in healthcare computing using machine learning and Python Vikas (Vik) Kumar BIRMINGHAM - MUMBAI Healthcare Analytics Made Simple. .. In short, we will be covering the following topics in this chapter: Basics of healthcare analytics History of healthcare analytics Examples of healthcare analytics Introduction to Anaconda, Jupyter Notebook, and SQLite What is healthcare analytics? Unfortunately, a definition of healthcare analytics is not in Webster's dictionary yet

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Mục lục

  • CONTENT

    • Download the example code files

    • Using visualizations to elucidate patient care

    • Predicting future diagnostic and treatment events

    • Installing a text editor

    • Healthcare Foundations

      • Healthcare delivery in the US

      • Machine Learning Foundations

        • Model frameworks for medical decision making

          • Tree-like reasoning

            • Categorical reasoning with algorithms and trees

            • Corresponding machine learning algorithms – decision tree and random forest

            • Probabilistic reasoning and Bayes theorem

              • Using Bayes theorem for calculating clinical probabilities

              • Calculating the baseline MIprobability

              • 2 x 2 contingency table for chest pain and myocardial infarction

              • Interpreting the contingency table and calculating sensitivity and specificity

              • Calculating likelihood ratios for chest pain (+ and -)

              • Calculating the post-test probability of MI given the presence of chest pain

              • Corresponding machine learning algorithm – the Naive Bayes Classifier

              • Criterion tables and the weighted sum approach

                • Criterion tables

                • Corresponding machine learning algorithms – linear and logistic regression

                • Pattern association and neural networks

                  • Complex clinical reasoning

                  • Corresponding machine learning algorithm – neural networks and deep learning

                  • Machine learning pipeline

                    • Loading the data

                    • Cleaning and preprocessing the data

                      • Aggregating data

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