Computational Models for Biomedical Reasoning and Problem Solving

Computational Models for Biomedical Reasoning and Problem Solving

Chung-Hao Chen, Sen-Ching Samson Cheung
Release Date: April, 2019|Copyright: © 2019 |Pages: 353
DOI: 10.4018/978-1-5225-7467-5
ISBN13: 9781522574675|ISBN10: 1522574670|EISBN13: 9781522574682
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Description & Coverage
Description:

The results of computational model simulations allow researchers and clinicians to make predictions about what will happen in the biological systems that are being studied in response to changing conditions for a disease or disorder. With a well-developed computational model, researchers and clinicians can better understand the cause of a disease or a disorder and predict treatment results.

Computational Models for Biomedical Reasoning and Problem Solving is a critical scholarly publication that provides insightful strategies to developing computational models that allow for the better understanding and treatment of various diseases and disorders. Featuring topics such as biomedicine, neuroscience, and artificial intelligence, this book is ideal for practitioners, clinicians, researchers, psychologists, and engineers.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • Bioinformatics
  • Biomedicine
  • Disease Modelling
  • Epidemiology
  • Healthcare Systems
  • Imaging Techniques
  • Medicine
  • Neuroimaging
  • Neuroscience
  • Signal Processing
  • Therapy
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Editor/Author Biographies

Chung-Hao Chen received his Ph.D. in Electrical Engineering at the University of Tennessee, Knoxville in August 2009, and his B.S. and M.S. in Computer Science and Information Engineering from Fu-Jen Catholic University, Taiwan in 1997 and 1999, respectively. In April 2001, he joined the Panasonic Taiwan Laboratory Company, Ltd. as a research and development engineer where he remained until August 2003. In August 2009, he joined in the department of Math and Computer Science at North Carolina Central University as an assistant professor. Since August 2011, he joins in the department of Electrical and Computer Engineering at Old Dominion University and he is currently an associate professor. His research interests include robotics, automated surveillance systems, pattern recognition, image processing, artificial intelligent systems, data analysis and mining, and network performance analysis. He has published more than 70 peer reviewed articles.

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