Synopsis
Despite the remarkable progress witnessed in the last decade in big data utilization and parallel processing techniques, a persistent disparity exists between the capabilities of computer-aided diagnosis systems and the intricacies of practical healthcare scenarios. This disconnection is particularly evident in the complex landscape of artificial intelligence (AI) and IoT innovations within the biomedical realm. The need to bridge this gap and explore the untapped potential in healthcare and biomedical applications has never been more crucial. As we navigate through these challenges, Applications of Parallel Data Processing for Biomedical Imaging offers insights and solutions to reshape the future of biomedical research. The objective of Applications of Parallel Data Processing for Biomedical Imaging is to bring together researchers from both the computer science and biomedical research communities. By showcasing state-of-the-art deep learning and large data analysis technologies, the book provides a platform for the cross-pollination of ideas between AI-based and traditional methodologies. The collaborative effort seeks to have a substantial impact on data mining, AI, computer vision, biomedical research, healthcare engineering, and other related fields. This interdisciplinary approach positions the book as a cornerstone for scholars, professors, and professionals working in software and medical fields, catering to both graduate and undergraduate students eager to explore the evolving landscape of parallel computing, artificial intelligence, and their applications in biomedical research.
À propos des auteurs
Rijwan Khan received his B. Tech Degree in Computer Science & Engineering from BIT, M. Tech in Computer Science & Engineering from IETE, and Ph.D.in Computer Engineering from Jamia Millia Islamia, New Delhi. He has 17 years of Academic & Research Experience in various areas of Computer Science. He is currently working as Professor and Program Chair of Department Computer Science and Engineering B.Tech 2nd Year at Galgotias University, G.B. Nagar U.P. He is author of three subject books. He published more than 30 research papers in different journals and conferences. He has been nominated in the board of reviewers of various peer-reviewed and refereed Journals. He is Editor of five research books. He is Editor of seven special issues of SCI and Scopus indexed journals. He was session chaired in three International conferences & Keynote speakers in some the national and International conferences
Indrajeet Kumar received his B Tech in Computer Science & Engineering from Sant Longowal Institute of Engineering and Technology, Punjab in 2009 and M Tech in Computer Engineering with specialization in Computer Network from YMCA University of Science & technology, Faridabad in 2013. He received his PhD on Analysis and Classification of Breast density classification using Mammographic images from GB Pant Institute of Engineering & Technology, Ghurdauri, Uttarakhand, India in 2019. During his PhD he worked on enhancing the potential of most commonly available Breast density classification for differential diagnosis between atypical cases of focal density cases. He served in academia in various reputed organizations like Galgotias Institutions, Greater Noida, U.P, India and graphic era hill University, Dehradun, India, for 6 years. His research interests include application of machine learning, Deep Learning and soft computing techniques for analysis of medical images.
Pushkar Praveen has a passion for technology which started early in their academic career, and they have spent countless hours honing skills and knowledge through online courses, seminars, and work on personal projects to build a solid foundation. Favorite Quote: " The only limit to our realization of tomorrow will be our doubts of today " by Franklin D. Roosevelt. They believe the only thing standing between them and goals is self-doubt. "By believing in myself and taking action toward my dreams, I can achieve anything I set my mind to." - Pushkar Praveen
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