Bris R., Majernik J., Pancerz K., Zaitseva E. (eds.) Application of Computational Intelligence in Biomedical Technology

Springer, 2016. — 255 p.Biomedical Technology represents one of the most dynamically developed scientific area that supports research activities aimed to discover, create and develop innovative applications of technological solutions to handle different biomedical problems. Technology development often requires multidisciplinary and teamoriented approaches and may lead to the realization of new and/or improved instruments that have substantial influence on quality and reliability of medical and biomedical progress and further research. In general, the Biomedical Technologies developed by technicians are transferred into practice by specialists in medicine. Here, the physicians utilize such technologies mainly to help their patients solve
their health problems as best as possible and return them back to normal life as soon as possible. On the other hand, the managers of various institutions included in the healthcare system can create proper conditions to support physicians in their innovative and advanced work by accepting of new methods and by personal or even financial interventions. Computational Intelligence and Informatics play a dominant role in Biomedical Technologies as it is an actual.
The authors of these book chapters discuss a lot of specific aspects of development methods and algorithms in Biomedical and Medical Informatics. Algorithms for medical image processing, modelling methods and tool, medical decision-making support, estimation of risks of treatments, reliability of medical systems, problems of practical clinical applications and many other topics are covered by individual contributions. Decisions of different problems in development of medical decision-making support system are presented. For example, decision-making process connected with the choice of right operation technique plays a big role as a risk decreasing factor taking into account the risk of post-operative mortality and morbidity as well. Having a good mathematical (statistical) model a decision-maker can assess and predict results of the expensive
Phadiatop medical test. Cox analysis can be used as a useful tool for the incidence of cancer, etc. Interesting results are discussed for estimation of risk in treatment and examination of reliability of medical system.Mesh-Based Modeling of Individual Cells and Their Dynamics in Biological Fluids
Usage of Industrial Computed Tomography for Evaluation of Custom-Made Implants
Assessment of Mortality Risk for Patients Undergoing Colorectal Surgery Using Regression Modeling
Profiling of Software Requirements for the Pharmaceutical Enterprise Manufacturing Execution System
Application of Survival Analysis on Analysing the Association Between Chromosomal Aberrations and Carcinoma
Modelling the Results of the Phadiatop Test Using the Logistic and Ordinal Regression
Complex Data Management in MRI Results Processing
Biometrics for Biomedical Applications
Multimedia Support of Medical Education Utilizing On-Line Archive of Video Lectures
Evaluation of Postural Stability Using Motion Analysis Techniques
Some Issues on an Object-Oriented Programming Language for Physarum Machines
A Tool for Computer-Aided Diagnosis of Psychological Disorders Based on the MMPI Test: An Overview
The Instance and Feature Selection for Neural Network Based Diagnosis of Chronic Obstructive Bronchitis
New Methods for the Reliability Analysis of Healthcare System Based on Application of Multi-State System