Search results for: Healthcare Analytics Made Simple

Healthcare Analytics Made Simple PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Healthcare Analytics Made Simple PDF full book. Access full book title Healthcare Analytics Made Simple by Vikas (Vik) Kumar. Download full books in PDF and EPUB format.

Healthcare Analytics Made Simple

Healthcare Analytics Made Simple PDF Author: Vikas (Vik) Kumar
Publisher: Packt Publishing Ltd
ISBN: 1787283224
Category : Computers
Languages : en
Pages : 268

Get Book

Book Description
Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Perform healthcare analytics with Python and SQL Build predictive models on real healthcare data with pandas and scikit-learn Use analytics to improve healthcare performance Book Description 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. What you will learn Gain valuable insight into healthcare incentives, finances, and legislation Discover the connection between machine learning and healthcare processes Use SQL and Python to analyze data Measure healthcare quality and provider performance Identify features and attributes to build successful healthcare models Build predictive models using real-world healthcare data Become an expert in predictive modeling with structured clinical data See what lies ahead for healthcare analytics Who this book is for Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.

Healthcare Analytics Made Simple

Healthcare Analytics Made Simple PDF Author: Vikas (Vik) Kumar
Publisher: Packt Publishing Ltd
ISBN: 1787283224
Category : Computers
Languages : en
Pages : 268

View

Book Description
Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Perform healthcare analytics with Python and SQL Build predictive models on real healthcare data with pandas and scikit-learn Use analytics to improve healthcare performance Book Description 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. What you will learn Gain valuable insight into healthcare incentives, finances, and legislation Discover the connection between machine learning and healthcare processes Use SQL and Python to analyze data Measure healthcare quality and provider performance Identify features and attributes to build successful healthcare models Build predictive models using real-world healthcare data Become an expert in predictive modeling with structured clinical data See what lies ahead for healthcare analytics Who this book is for Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.

Machine Learning for Healthcare Analytics Projects

Machine Learning for Healthcare Analytics Projects PDF Author: Eduonix Learning Solutions
Publisher: Packt Publishing Ltd
ISBN: 1789532523
Category : Computers
Languages : en
Pages : 134

View

Book Description
Create real-world machine learning solutions using NumPy, pandas, matplotlib, and scikit-learn Key FeaturesDevelop a range of healthcare analytics projects using real-world datasetsImplement key machine learning algorithms using a range of libraries from the Python ecosystemAccomplish intermediate-to-complex tasks by building smart AI applications using neural network methodologiesBook Description Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics. This book will teach you how to implement key machine learning algorithms and walk you through their use cases by employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors (KNN) models. In the final chapters, you will create a deep neural network in Keras to predict the onset of diabetes in a huge dataset of patients. You will also learn how to predict heart diseases using neural networks. By the end of this book, you will have learned how to address long-standing challenges, provide specialized solutions for how to deal with them, and carry out a range of cognitive tasks in the healthcare domain. What you will learnExplore super imaging and natural language processing (NLP) to classify DNA sequencingDetect cancer based on the cell information provided to the SVMApply supervised learning techniques to diagnose autism spectrum disorder (ASD)Implement a deep learning grid and deep neural networks for detecting diabetesAnalyze data from blood pressure, heart rate, and cholesterol level tests using neural networksUse ML algorithms to detect autistic disordersWho this book is for Machine Learning for Healthcare Analytics Projects is for data scientists, machine learning engineers, and healthcare professionals who want to implement machine learning algorithms to build smart AI applications. Basic knowledge of Python or any programming language is expected to get the most from this book.

Advanced Intelligent Systems for Sustainable Development (AI2SD’2019)

Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) PDF Author: Mostafa Ezziyyani
Publisher: Springer Nature
ISBN: 3030366642
Category : Technology & Engineering
Languages : en
Pages : 407

View

Book Description
This book highlights the latest research in the fields of health care and agriculture, presented at the second installment of the International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD-2019), held on July 08–11, 2019 in Marrakech, Morocco. Gathering contributions by respected researchers in the field of agriculture, the book is intended to stimulate debate in this field, and proposes new solutions, tools and effective techniques concerning various current topics in the field of agriculture, such as ICT, IoT and big data analytics for agriculture, smart systems for plant productivity, and data analytics of socio-economic dimensions for sustainable agriculture and aquaculture. With regard to the field of health, the book addresses several areas of research, including E-health services in smart environments (smart homes, smart medical institutions, smart cities), E-health and big data analysis, IoT for health, network interoperability in E-health ecosystems, current and emerging web norms and communication technologies for E-health, heterogeneity of E-health environments and platforms (sensors and actuators, heterogeneous access technologies, security), human–computer interaction, RFID and localization techniques, E-health virtual communities, and business intelligence in health care. This book is intended for academic and professional researchers, decision-makers and all stakeholders in the fields of health and agriculture whose work involves the development and improvement of this field with modern I4.0 technologies and approaches. The authors of each chapter report on the state of the art and present the outcomes of their own research, laboratory experiments, and successful applications. The purpose of the book is to combine the idea of advanced intelligent systems with appropriate tools and techniques for modeling, management, and decision support in the fields of health and agriculture.

Data Visualization Made Simple

Data Visualization Made Simple PDF Author: Kristen Sosulski
Publisher: Routledge
ISBN: 135138077X
Category : Business & Economics
Languages : en
Pages : 272

View

Book Description
Data Visualization Made Simple is a practical guide to the fundamentals, strategies, and real-world cases for data visualization, an essential skill required in today’s information-rich world. With foundations rooted in statistics, psychology, and computer science, data visualization offers practitioners in almost every field a coherent way to share findings from original research, big data, learning analytics, and more. In nine appealing chapters, the book: examines the role of data graphics in decision-making, sharing information, sparking discussions, and inspiring future research; scrutinizes data graphics, deliberates on the messages they convey, and looks at options for design visualization; and includes cases and interviews to provide a contemporary view of how data graphics are used by professionals across industries Both novices and seasoned designers in education, business, and other areas can use this book’s effective, linear process to develop data visualization literacy and promote exploratory, inquiry-based approaches to visualization problems.

Intelligent Systems and Applications

Intelligent Systems and Applications PDF Author: Kohei Arai
Publisher: Springer Nature
ISBN: 3030821994
Category : Artificial intelligence
Languages : en
Pages : 901

View

Book Description
This book presents Proceedings of the 2021 Intelligent Systems Conference which is a remarkable collection of chapters covering a wider range of topics in areas of intelligent systems and artificial intelligence and their applications to the real world. The conference attracted a total of 496 submissions from many academic pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-review process. Of the total submissions, 180 submissions have been selected to be included in these proceedings. As we witness exponential growth of computational intelligence in several directions and use of intelligent systems in everyday applications, this book is an ideal resource for reporting latest innovations and future of AI. The chapters include theory and application on all aspects of artificial intelligence, from classical to intelligent scope. We hope that readers find the book interesting and valuable; it provides the state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research.

Healthcare Analytics for Quality and Performance Improvement

Healthcare Analytics for Quality and Performance Improvement PDF Author: Trevor L. Strome
Publisher: John Wiley & Sons
ISBN: 1118760158
Category : Business & Economics
Languages : en
Pages : 240

View

Book Description
Improve patient outcomes, lower costs, reduce fraud—allwith healthcare analytics Healthcare Analytics for Quality and PerformanceImprovement walks your healthcare organization from relying ongeneric reports and dashboards to developing powerful analyticapplications that drive effective decision-making throughout yourorganization. Renowned healthcare analytics leader Trevor Stromereveals in this groundbreaking volume the true potential ofanalytics to harness the vast amounts of data being generated inorder to improve the decision-making ability of healthcare managersand improvement teams. Examines how technology has impacted healthcare delivery Discusses the challenge facing healthcare organizations: toleverage advances in both clinical and information technology toimprove quality and performance while containing costs Explores the tools and techniques to analyze and extract valuefrom healthcare data Demonstrates how the clinical, business, and technologycomponents of healthcare organizations (HCOs) must work together toleverage analytics Other industries are already taking advantage of big data.Healthcare Analytics for Quality and Performance Improvementhelps the healthcare industry make the most of the precious dataalready at its fingertips for long-overdue quality and performanceimprovement.

Machine Learning Techniques for Improved Business Analytics

Machine Learning Techniques for Improved Business Analytics PDF Author: G., Dileep Kumar
Publisher: IGI Global
ISBN: 1522535357
Category : Business & Economics
Languages : en
Pages : 286

View

Book Description
Analytical tools and algorithms are essential in business data and information systems. Efficient economic and financial forecasting in machine learning techniques increases gains while reducing risks. Providing research on predictive models with high accuracy, stability, and ease of interpretation is important in improving data preparation, analysis, and implementation processes in business organizations. Machine Learning Techniques for Improved Business Analytics is a collection of innovative research on the methods and applications of artificial intelligence in strategic business decisions and management. Featuring coverage on a broad range of topics such as data mining, portfolio optimization, and social network analysis, this book is ideally designed for business managers and practitioners, upper-level business students, and researchers seeking current research on large-scale information control and evaluation technologies that exceed the functionality of conventional data processing techniques.

Research Anthology on Big Data Analytics, Architectures, and Applications

Research Anthology on Big Data Analytics, Architectures, and Applications PDF Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1668436639
Category : Computers
Languages : en
Pages : 1988

View

Book Description
Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Unstructured Data Analytics

Unstructured Data Analytics PDF Author: Jean Paul Isson
Publisher: John Wiley & Sons
ISBN: 1119129753
Category : Computers
Languages : en
Pages : 432

View

Book Description
Turn unstructured data into valuable business insight Unstructured Data Analytics provides an accessible, non-technical introduction to the analysis of unstructured data. Written by global experts in the analytics space, this book presents unstructured data analysis (UDA) concepts in a practical way, highlighting the broad scope of applications across industries, companies, and business functions. The discussion covers key aspects of UDA implementation, beginning with an explanation of the data and the information it provides, then moving into a holistic framework for implementation. Case studies show how real-world companies are leveraging UDA in security and customer management, and provide clear examples of both traditional business applications and newer, more innovative practices. Roughly 80 percent of today's data is unstructured in the form of emails, chats, social media, audio, and video. These data assets contain a wealth of valuable information that can be used to great advantage, but accessing that data in a meaningful way remains a challenge for many companies. This book provides the baseline knowledge and the practical understanding companies need to put this data to work. Supported by research with several industry leaders and packed with frontline stories from leading organizations such as Google, Amazon, Spotify, LinkedIn, Pfizer Manulife, AXA, Monster Worldwide, Under Armour, the Houston Rockets, DELL, IBM, and SAS Institute, this book provide a framework for building and implementing a successful UDA center of excellence. You will learn: How to increase Customer Acquisition and Customer Retention with UDA The Power of UDA for Fraud Detection and Prevention The Power of UDA in Human Capital Management & Human Resource The Power of UDA in Health Care and Medical Research The Power of UDA in National Security The Power of UDA in Legal Services The Power of UDA for product development The Power of UDA in Sports The future of UDA From small businesses to large multinational organizations, unstructured data provides the opportunity to gain consumer information straight from the source. Data is only as valuable as it is useful, and a robust, effective UDA strategy is the first step toward gaining the full advantage. Unstructured Data Analytics lays this space open for examination, and provides a solid framework for beginning meaningful analysis.

Leveraging Data in Healthcare

Leveraging Data in Healthcare PDF Author: Rebecca Mendoza Saltiel Busch
Publisher: CRC Press
ISBN: 1498757731
Category : Business & Economics
Languages : en
Pages : 215

View

Book Description
The healthcare industry is in a state of accelerated transition. The proliferation of data and its assimilation, access, use, and security are ever-increasing challenges. Finding ways to operationalize business and clinical data management in the face of government and market mandates is enough to keep most chief officers up at night! Leveraging Data in Healthcare: Best Practices for Controlling, Analyzing, and Using Data argues that the key to survival for any healthcare organization in today’s data-saturated market is to fundamentally redefine the roles of chief information executives—CIOs, CFOs, CMIOs, CTOs, CNIOs, CTOs and CDOs—from suppliers of data to drivers of data intelligence. This book presents best practices for controlling, analyzing, and using data. The elements of preparing an actionable data strategy are exemplified on subjects such as revenue integrity, revenue management, and patient engagement. Further, the book illustrates how to operationalize the electronic integration of health and financial data within patient financial services, information management services, and patient engagement activities. An integrated environment will activate a data-driven intelligent decision support infrastructure. The increasing impact of consumer engagement will continue to affect the organization’s bottom line. Success in this new world will need collaboration among the chiefs, users, and data creators.