Reviews
"Anyone with experience in data analytics who is coming into the field of healthcare should make time to read this book ..." --Computing Reviews "... an outstanding book that contains a resourceful introduction to fundamental knowledge in data sources and basic analysis, as well as a presentation of updated research with respect to data analytic methods and applications in healthcare practice. The book balances the various levels of detail to meet the needs of researchers and practitioners with diverse backgrounds and interests. ... a highly recommended book for those who wish to explore the healthcare data analytics domain." --Journal of Biomedical Informatics, 58, 2015, "... an outstanding book that contains a resourceful introduction to fundamental knowledge in data sources and basic analysis, as well as a presentation of updated research with respect to data analytic methods and applications in healthcare practice. The book balances the various levels of detail to meet the needs of researchers and practitioners with diverse backgrounds and interests. ... a highly recommended book for those who wish to explore the healthcare data analytics domain." --Journal of Biomedical Informatics, 58, 2015, "Anyone with experience in data analytics who is coming into the field of healthcare should make time to read this book ..." --Computing Reviews "... an outstanding book that contains a resourceful introduction to fundamental knowledge in data sources and basic analysis, as well as a presentation of updated research with respect to data analytic methods and applications in healthcare practice. The book balances the various levels of detail to meet the needs of researchers and practitioners with diverse backgrounds and interests. ... a highly recommended book for those who wish to explore the healthcare data analytics domain." --Journal of Biomedical Informatics, 58, 2015 "The volume Healthcare Data Analytics by Reddy and Aggarwal is more technical and gives a comprehensive introduction to fundamental principles, algorithms, and applications of health data acquisition, processing, and analysis. It starts with a survey on electronic health records (EHR), a central instrument for collecting heath data and putting hese data into context. The next chapters present biomedical image data, sensor data, genomic data, and the processing of clinical text by natural language processing (NLP). Further relevant sources of health data are the biomedical literature and social media. Chapter 10 is on clinical prediction models and offers the classical biostatistical toolbox. Over the next three chapters, more complex models based on longitudinal, spatial, and high-dimensional data are discussed. The presentation uses the machine-learning perspective but offers many references from the biostatistical literature. Chapter 14 discusses information retrieval for healthcare . Its overall goal is to find content which meets information needs. The interplay of two processes determines the success of information retrieval: Indexing assigns metadata to content items, retrieval produces content items based on the user's query. Evaluationstrategies for these processes are also discussed. My favoritepart of the book is chapter 15 privacy-preserving data publishing methods in healthcare ." --Ulrich Mansmann, Biometrics , December 2017, "Anyone with experience in data analytics who is coming into the field of healthcare should make time to read this book ..." --Computing Reviews "... an outstanding book that contains a resourceful introduction to fundamental knowledge in data sources and basic analysis, as well as a presentation of updated research with respect to data analytic methods and applications in healthcare practice. The book balances the various levels of detail to meet the needs of researchers and practitioners with diverse backgrounds and interests. ... a highly recommended book for those who wish to explore the healthcare data analytics domain." --Journal of Biomedical Informatics, 58, 2015 "The volume Healthcare Data Analytics by Reddy and Aggarwal is more technical and gives a comprehensive introduction to fundamental principles, algorithms, and applications of health data acquisition, processing, and analysis. It starts with a survey on electronic health records (EHR), a central instrument for collecting heath data and putting hese data into context. The next chapters present biomedical image data, sensor data, genomic data, and the processing of clinical text by natural language processing (NLP). Further relevant sources of health data are the biomedical literature and social media. Chapter 10 is on clinical prediction models and offers the classical biostatistical toolbox. Over the next three chapters, more complex models based on longitudinal, spatial, and high-dimensional data are discussed. The presentation uses the machine-learning perspective but offers many references from the biostatistical literature. Chapter 14 discusses information retrieval for healthcare . Its overall goal is to find content which meets information needs. The interplay of two processes determines the success of information retrieval: Indexing assigns metadata to content items, retrieval produces content items based on the user's query. Evaluat
