MATLAB Programming for Biomedical Engineers and Scientists, Second Edition provides an easy-to-learn introduction to the fundamentals of computer programming in MATLAB. The book explains the principles of good programming practice, while also demonstrating how to write efficient and robust code that analyzes and visualizes biomedical data. Aimed at the biomedical engineering student, biomedical scientist and medical researcher with little or no computer programming experience, this is an excellent resource for learning the principles and practice of computer programming using MATLAB. The book enables the reader to analyze problems and apply structured design methods to produce elegant, efficient and well-structured program designs, implement a structured program design in MATLAB, write code that makes good use of MATLAB programming features, including control structures, functions and advanced data types, and much more. - Presents many real-world biomedical problems and data, showing the practical application of programming concepts - Contains two whole chapters dedicated to the practicalities of designing and implementing more complex programs - Provides an accompanying website with freely available data and source code for the practical code examples, activities and exercises in the book - Includes new chapters on machine learning, engineering mathematics, and expanded coverage of data types

This book focuses on the role of computers in the provision of medical services. It provides both a conceptual framework and a practical approach for the implementation and management of IT used to improve the delivery of health care. Inspired by a Stanford University training program, it fills the need for a high quality text in computers and medicine. It meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Completely revised and expanded, this work includes several new chapters filled with brand new material.

Resource added for the Health Information Technology program 105301.

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Over 900 references to monographic and journal literature about the use of computers in biology and medicine. Emphasis in the annotations is on computer applications, rather than on methods and results generally common to authors' abstracts. Entries arranged by topics under bibliographies, monographs, and articles. Author, subject indexes.