Description:
Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference.
Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information.
Brief description: Dr. Sudipta Roy received his Ph.D. in Computer Science & Engineering from the Department of Computer Science and Engineering, University of Calcutta. He is author of more than forty publications in refereed national / international journals and conferences. Dr. Roy holds a US patent in medical image processing, and filed an Indian patent in smart agricultural systems. Dr. Roy serves as an Associate Editor of IEEE Access, and IEEE and International Journal of Computer Vision and Image Processing (IJCVIP). His fields of research interest are biomedical image analysis, image processing, steganography, artificial intelligence, big data analysis, machine learning and big data technologies. Currently, he is a Research Associate at PRTTL, Washington University in St. Louis, Saint Louis, MO, USA