Librería Portfolio

At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available to solve healthcare problems.

The book details novel techniques for acquiring, handling, retrieving, and making best use of healthcare data. It analyzes recent developments in healthcare computing and discusses emerging technologies that can help improve the health and well-being of patients.

Written by prominent researchers and experts working in the healthcare domain, the book sheds light on many of the computational challenges in the field of medical informatics. Each chapter in the book is structured as a ´survey-style´ article discussing the prominent research issues and the advances made on that research topic. The book is divided into three major categories:

Healthcare Data Sources and Basic Analytics - details the various healthcare data sources and analytical techniques used in the processing and analysis of such data
Advanced Data Analytics for Healthcare - covers advanced analytical methods, including clinical prediction models, temporal pattern mining methods, and visual analytics
Applications and Practical Systems for Healthcare - covers the applications of data analytics to pervasive healthcare, fraud detection, and drug discovery along with systems for medical imaging and decision support
Computer scientists are usually not trained in domain-specific medical concepts, whereas medical practitioners and researchers have limited exposure to the data analytics area. The contents of this book will help to bring together these diverse communities by carefully and comprehensively discussing the most relevant contributions from each domain.



An Introduction to Healthcare Data Analytics; Chandan K. Reddy and Charu C. Aggarwal

Introduction

Healthcare Data Sources and Basic Analytics

Advanced Data Analytics for Healthcare

Applications and Practical Systems for Healthcare

Resources for Healthcare Data Analytics

Conclusions

HEALTHCARE DATA SOURCES AND BASIC ANALYTICS


Electronic Health Records: A Survey; Rajiur Rahman and Chandan K. Reddy

Introduction

History of EHR

Components of HER

Coding Systems

Benefits of EHR

Barriers to Adopting EHR

Challenges of Using EHR Data

Phenotyping Algorithms

Conclusions


Biomedical Image Analysis; Dirk Padfield, Paulo Mendonca, and Sandeep Gupta

Introduction

Biomedical Imaging Modalities

Object Detection

Image Segmentation

Image Registration

Feature Extraction

Conclusion and Future Work


Mining of Sensor Data in Healthcare: A Survey; Daby Sow, Kiran K. Turaga, Deepak S. Turaga, and Michael Schmidt

Introduction

Mining Sensor Data in Medical Informatics: Scope and Challenges

Challenges in Healthcare Data Analysis

Sensor Data Mining Applications

Nonclinical Healthcare Applications

Summary and Concluding Remarks


Biomedical Signal Analysis; Abhijit Patil, Rajesh Langoju, Suresh Joel, Bhushan D. Patil, and Sahika Genc

Introduction

Types of Biomedical Signals

ECG Signal Analysis.

Denoising of Signals

Multivariate Biomedical Signal Analysis

Cross-Correlation Analysis

Recent Trends in Biomedical Signal Analysis

Discussions

Genomic Data Analysis for Personalized Medicine; Juan Cui

Introduction

Genomic Data Generation

Methods and Standards for Genomic Data Analysis

Types of Computational Genomics Studies towards Personalized Medicine

Genetic and Genomic Studies to theBedside of Personalized Medicine

Concluding Remarks


Natural Language Processing and Data Mining for Clinical Text; Kalpana Raja and Siddhartha R. Jonnalagadda

Introduction

Natural Language Processing

Mining Information from Clinical Text

Challenges of Processing Clinical Reports

Clinical Applications

Conclusions


Mining the Biomedical Literature; Claudiu Mihaila, Riza Batista-Navarro, Noha Alnazzawi, Georgios Kontonatsios, Ioannis Korkontzelos, Rafal Rak, Paul Thompson, and Sophia Ananiadou

Introduction

Resources

Terminology Acquisition and Management

InformationExtraction

Discourse Interpretation

Text Mining Environments

Applications

Integration with Clinical Text Mining

Conclusions


Social Media Analytics for Healthcare; Alexander Kotov

Introduction

Social Media Analysis for Detection and Tracking of Infectious Disease

Social Media Analysis for Public Health Research

Analysis of Social Media Use in Healthcare

Conclusions and Future Directions

ADVANCED DATA ANALYTICS FOR HEALTHCARE


A Review of Clinical Prediction Models; Chandan K. Reddy and Yan Li

Introduction

Basic Statistical Prediction Models

Alternative Clinical Prediction Models

Survival Models

Evaluation and Validation

Conclusion


Temporal Data Mining for Healthcare Data; Iyad Batal

Introduction

Association Analysis

Temporal Pattern Mining

Sensor Data Analysis

Other Temporal Modeling Methods

Resources

Summary


Visual Analytics for Healthcare; David Gotz, Jesus Caban, and Annie T. Chen

Introduction

Introduction to Visual Analytics and Medical Data Visualization

Visual Analytics in Healthcare

Conclusion

Predictive Models for Integrating Clinical and Genomic Data; Sanjoy Dey, Rohit Gupta, Michael Steinbach, and Vipin Kumar

Introduction

Issues and Challenges in Integrating Clinical and Genomic Data

Different Types of Integration

Different Goals of Integrative Studies

Validation

Discussion and Future Work


Information Retrieval for Healthcare; William R. Hersh

Introduction

Knowledge-Based Information in Healthcare and Biomedicine

Content of Knowledge-Based Information Resources

Indexing

Retrieval

Evaluation

Research Directions

Conclusion


Privacy-Preserving Data Publishing Methods in Healthcare; Yubin Park and Joydeep Ghosh

Introduction

Data Overview and Preprocessing

Privacy-Preserving Publishing Methods

Challenges with Health Data

Conclusion

APPLICATIONS AND PRACTICAL SYSTEMS FOR HEALTHCARE

Data Analytics for Pervasive Health; Giovanni Acampora, Diane J. Cook, Parisa Rashidi, and Athanasios V. Vasilakos

Introduction

Supporting Infrastructure and Technology

Basic Analytic Techniques

Advanced Analytic Techniques

Applications

Conclusions and Future Outlook


Fraud Detection in Healthcare; Varun Chandola, Jack Schryver, and Sreenivas Sukumar

Introduction

Understanding Fraud in the Healthcare System

Definition and Types of Healthcare Fraud

Identifying Healthcare Fraud from Data

Knowledge Discovery-Based Solutions for Identifying Fraud

Conclusions


Data Analytics for Pharmac