دانلود کتاب Computer Intensive Methods in Statistics

This class-tested textbook is designed for a semester-long graduate, or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics. It integrates computer science and clinical perspectives. The book prepares computer science students for careers in computational health informatics and medical data analysis. Features Integrates computer science and clinical perspectives. Describes various statistical and artificial intelligence techniques including machine learning techniques such as clustering including temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining widely used in health-data analysis. Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange. Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development. Arvind Bansal is a full professor of Computer Science at Kent State University, Kent, Ohio, USA. He received his PhD (1988) from Case Western Reserve University, Cleveland, Ohio, USA. His research publications, and undergraduate and graduate teaching are in artificial intelligence, multimedia systems and languages, bioinformatics, and computational health informatics. Javed Khan is a full professor of Computer Science at Kent State University, Kent, Ohio, USA. He received his PhD (1995) from University of Hawaii at Manoa, USA. His research publications, and undergraduate and graduate teachings are in artificial intelligence, computer networking protocols, educational networks, medical image processing and communication, perceptual enhancement, and automated knowledge acquisition. He has been a long-term Fulbright area expert. S. Kaisar Alam received his PhD (1996) in Electrical Engineering from University of Rochester, Rochester NY, USA. His research publications and teaching are in medical image analysis and genome analysis. He was a member of the research staff in Biomedical Engineering Laboratories during 1998-2013. He has been a Fullbright scholar and a visiting professor at RUTGERS University, NY, USA. Currently, he runs his company for medical image analysis.