In the current scenario of Forensic Science and Criminal Investigation, experts are facing many challenges due to huge amounts of data, tiny pieces of evidence in the chaotic and complex environment, traditional laboratory structures and sometimes insufficient knowledge which may lead to failure of investigation or miscarriage of justice. Artificial Intelligence and imaging technologies are the promising solutions to address these challenges with case based reasoning for errorless, objective and reproducible results in various fields of forensics. This book will not only provide a platform for researchers to present state of the art technologies, but will be a reference for law enforcement to use for crime investigation along with researchers in the field .

Within modern forensic science and criminal investigation, experts face several challenges including managing huge amounts of data, handling miniscule pieces of evidence in a chaotic and complex environment, navigating traditional laboratory structures, and, sometimes, dealing with insufficient knowledge. These challenges must be overcome to avoid failure in investigation or miscarriage of justice. Technologies to Advance Automation in Forensic Science and Criminal Investigation provides a platform for researchers to present state-of-the-art technologies within forensic science and criminal investigation. Covering topics such as financial fraud, machine learning, and source camera identification, this book is an essential reference for criminal investigators, justice departments, law enforcement, legislators, computer scientists, automation professionals, researchers, academicians, and students and educators in higher education.

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.