Computational Medicine

Computational methodologies and modeling play a growing role for investigating mechanisms, and for the diagnosis and therapy of human diseases. This progress gave rise to computational medicine, an interdisciplinary field at the interface of computer science and medicine. The main focus of computational medicine lies in the development of data analysis methods and mathematical modeling as well as computational simulation techniques specifically addressing medical problems. In this book, we present a number of computational medicine topics at several scales: from molecules to cells, organs, and organisms. At the molecular level, tools for the analysis of genome variations as well as cloud computing resources for medical genetics are reviewed. Then, an analysis of gene expression data and the application to the characterization of microbial communities are highlighted. At the protein level, two types of analyses for mass spectrometry data are reviewed: labeled quantitative proteomics and lipidomics, followed by protein sequence analysis and a 3D structure and drug design chapter. Finally, three chapters on clinical applications focus on the integration of biomolecular and clinical data for cancer research, biomarker discovery, and network-based methods for computational diagnostics.

This three volume series represents a selected and refereed collection of papers contributed by the participants of the First World Congress on Computational Medicine, Public Health, and Biotechnology, held in 1994 at Austin, Texas. Over 500 individuals, from 30 countries attended this meeting. In addition, this collection contains a number of papers from the Australian CSIRO High Performance Computing Meeting held that same year.

This book presents an overview of a variety of contemporary statistical, mathematical and computer science techniques which are used to further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets of clinical data typically found in patient’s medical records, image mining, medical mining, data mining and machine learning applied to generic genomic data and more. This work also introduces modeling behavior of cancer cells, multi-scale computational models and simulations of blood flow through vessels by using patient-specific models. The authors cover different imaging techniques used to generate patient-specific models. This is used in computational fluid dynamics software to analyze fluid flow. Case studies are provided at the end of each chapter. Professionals and researchers with quantitative backgrounds will find Computational Medicine in Data Mining and Modeling useful as a reference. Advanced-level students studying computer science, mathematics, statistics and biomedicine will also find this book valuable as a reference or secondary text book.

Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.

With considerations such as complex-dimensional geometries and nonlinearity, the computational solution of partial differential systems has become so involved that it is important to automate decisions that have been normally left to the individual. This book covers such decisions: 1) mesh generation with links to the software generating the domain geometry, 2) solution accuracy and reliability with mesh selection linked to solution generation. This book is suited for mathematicians, computer scientists and engineers and is intended to encourage interdisciplinary interaction between the diverse groups.

One of the greatest challenges facing the computational engineering community is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, the biomedical sciences and medicine. The Computational Biomechanics for Medicine series provides an opportunity for specialists in computational biomechanics to present their latest methodologies and advancements. This 5th edition comprises nine of the latest developments in both fundamental science and patient-specific applications, from researchers in Australia, New Zealand, USA, UK, France, Ireland and China. Some of the interesting topics discussed are: cellular mechanics; tumor growth and modeling; medical image analysis and both patient-specific fluid dynamics and solid mechanic simulations.

New technology always raises compelling ethical questions. As those in medicine increasingly depend on computers and other intelligent machines, the intersection of ethics, computing and the health professions grows much more complex and significant. This book attempts systematically to identify and address the full range of ethical issues that arise when intelligent machines are used in medicine, nursing, psychology, and allied health professions. It maps and explores a variety of important issues and controversies, including ethics and evaluation in computational medicine, patient and provider confidentiality, responsibility for use of computers in medicine, appropriate use of decision support systems, outcomes of research and computational prognosis (including mortality predictions), and computer-based biomedical research - especially meta-analysis. This book is accessible to participants in the fields of bioethics and medical informatics. It is appropriate for physicians, nurses, administrators, ethicists, health attorneys, advanced undergraduates and graduate students.