Modelling Degradation of Bioresorbable Polymeric Medical Devices

• Author : J Pan
• Publisher : Elsevier
• Release : 24 October 2014

The use of bioresorbable polymers in stents, fixation devices and tissue engineering is revolutionising medicine. Both industry and academic researchers are interested in using computer modelling to replace some experiments which are costly and time consuming. This book provides readers with a comprehensive review of modelling polymers and polymeric medical devices as an alternative to practical experiments. Chapters in part one provide readers with an overview of the fundamentals of biodegradation. Part two looks at a wide range of degradation

• Author : C. A. Brebbia
• Publisher : WIT Press
• Release : 25 March 2023

The idea of preparing this volume originated from the ever increasing importance of computational modelling of complex problems in medicine. Considerable advances have been made in this area as demonstrated by the continued success of the International Conference on Modelling in Medicine and Biology organised by the Wessex Institute of Technology.The work reported at those meetings and the research carried out at the Wessex Institute of Technology indicated the increasing interaction and collaboration between medical and engineering scientists. Advances

• Author : Shu-Kay Ng
• Publisher : CRC Press
• Release : 03 May 2019

Mixture Modelling for Medical and Health Sciences provides a direct connection between theoretical developments in mixture modelling and their applications in real world problems. The book describes the development of the most important concepts through comprehensive analyses of real and practical examples taken from real-life research problems in

• Author : George Christakos,Dionissios Hristopulos
• Publisher : Springer Science & Business Media
• Release : 17 April 2013

Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus provides a holistic, conceptual and quantitative framework for Environmental Health Modelling in space-time. The holistic framework integrates two aspects of Environmental Health Science that have been previously treated separately: the environmental aspect, which involves the natural processes that bring about human exposure to harmful substances; and the health aspect, which focuses on the interactions of these substances with the human body. Some of the fundamental issues addressed in this work include variability, scale,

• Author : James K. Lindsey
• Publisher : Unknown
• Release : 25 March 2023

This text provides an introduction to the use of nonlinear models in medical statistics. It is a practical text rather than a theoretical one and assumes a basic knowledge of statistical modelling and of generalized linear models. It begins with a general introduction to nonlinear models, comparing them to generalized linear models, descriptions of data handling and formula definition and a summary of the principal types of nonlinear regression formulae. There is an emphasis on techniques for non-normal data. Following

• Author : Werner Vach
• Publisher : CRC Press
• Release : 27 November 2012

While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners. Regression Models as a Tool in Medical Research presents the fundamental concepts and important aspects of regression models most commonly used in medical research, including the classical regression model for continuous outcomes, the logistic regression model for binary outcomes, and the Cox proportional hazards model for survival data. The text emphasizes adequate use, correct

• Author : Helen Brown,Robin Prescott
• Publisher : John Wiley & Sons
• Release : 12 December 2014

A fully updated edition of this key text on mixed models, focusing on applications in medical research The application of mixed models is an increasingly popular way of analysing medical data, particularly in the pharmaceutical industry. A mixed model allows the incorporation of both fixed and random variables within a statistical analysis, enabling efficient inferences and more information to be gained from the data. There have been many recent advances in mixed modelling, particularly regarding the software and applications. This

• Author : Peter Schlattmann
• Publisher : Springer Science & Business Media
• Release : 02 March 2009

Patients are not alike! This simple truth is often ignored in the analysis of me- cal data, since most of the time results are presented for the “average” patient. As a result, potential variability between patients is ignored when presenting, e.g., the results of a multiple linear regression model. In medicine there are more and more attempts to individualize therapy; thus, from the author’s point of view biostatis- cians should support these efforts. Therefore, one of the tasks

• Author : Alexander Anderson,Katarzyna Rejniak
• Publisher : Springer Science & Business Media
• Release : 22 June 2007

Aimed at postgraduate students in a variety of biology-related disciplines, this volume presents a collection of mathematical and computational single-cell-based models and their application. The main sections cover four general model groupings: hybrid cellular automata, cellular potts, lattice-free cells, and viscoelastic cells. Each section is introduced by a discussion of the applicability of the particular modelling approach and its advantages and disadvantages, which will make the book suitable for students starting research in mathematical biology as well as scientists modelling

• Author : Thomas A. Gerds,Michael W. Kattan
• Publisher : CRC Press
• Release : 01 February 2021

Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient’s individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when

• Author : John R. Zaleski
• Publisher : Artech House
• Release : 25 March 2023

This cutting-edge volume is the first book that provides you with practical guidance on the use of medical device data for bioinformatics modeling purposes. You learn how to develop original methods for communicating with medical devices within healthcare enterprises and assisting with bedside clinical decision making. The book guides in the implementation and use of clinical decision support methods within the context of electronic health records in the hospital environment.This highly valuable reference also teaches budding biomedical engineers and

• Author : Amit Gefen
• Publisher : Springer Science & Business Media
• Release : 05 January 2012

This book reviews the frontier of research and clinical applications of Patient Specific Modeling, and provides a state-of-the-art update as well as perspectives on future directions in this exciting field. The book is useful for medical physicists, biomedical engineers and other engineers who are interested in the science and technology aspects of Patient Specific Modeling, as well as for radiologists and other medical specialists who wish to be updated about the state of implementation.

• Author : D. Cardus,C. Vallbona
• Publisher : Springer Science & Business Media
• Release : 08 March 2013

The papers gathered in this volume were presented at the medical sessions of the First Conference on Mathematics at the Service of Man held in Barcelona, Spain, July 11-16, 1977. Papers presented at the medical sessions were more numerous than those pre sented in any other single area of specialization covered in the conference. Because pf this, the Publications Committee resolved that papers presented at medical sessions be published separately from the proceedings of the conference. The proceedings of the conference

• Author : Douglas D. Gunzler,Adam T. Perzynski,Adam C. Carle
• Publisher : CRC Press
• Release : 12 April 2021

Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time

• Author : Judith R. Lave,Lester B. Lave,Samuel Leinhardt,Rand Corporation
• Publisher : Unknown
• Release : 25 March 1974