This book presents authoritative recent research on Biomedical Informatics, bringing together contributions from some of the most respected researchers in this field.
Biomedical Informatics represents a growing area of interest and innovation in the management of health-related data, and is essential to the development of focused computational models. Outlining the direction of current research, the book will be of considerable interest to theoreticians and application scientists alike. Further, as all chapters are self-contained, it also provides a valuable sourcebook for graduate students.
Advances in Biomedical Informatics: An Introduction.- Digital Health Research Methods and Tools.- Machine Learning for Structured Clinical Data.- Defining and Learning Interactive Causes.- Bayesian Network Modeling for Specific Health Checkups on Metabolic Syndrome.- Unsupervised Detection and Analysis of Changes in Everyday Physical Activity Data.- Machine Learning Applied to Optometry Data.- Intelligent Decision Support Systems in Automated Medical Diagnosis.- On the Automation of Medical Knowledge and Medical Decision Support Systems.- Vital Signs Telemonitoring by using Smart Body Area Networks, Mobile Devices and Advanced Signal Processing.- Preprocessing in High Dimensional Datasets.- Analysis of Questionnaire Survey on Psychic Characteristics in the Elderly Using Quantification Theory II.