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Multicore Computing
Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the advent of multicore architectures. However, programming multicore machines is much more difficult due to oddities existing in the architectures. Offering insights into different facets of this area, Multicore Computing: Algorithms, Architectures, and Applications focuses on the architectures, algorithms, and applications of multicore computing. It ...
Directory of Graduate Research
Faculties, publications and doctoral theses in departments or divisions of chemistry, chemical engineering, biochemistry and pharmaceutical and/or medicinal chemistry at universities in the United States and Canada.
Amino Acids, Peptides and Proteins
Amino Acids, Peptides and Proteins comprises a comprehensive review of significant developments at this biology/chemistry interface. Each volume of this Specialist Periodical Report opens with an overview of amino acids and their applications. Volume 37 marks the return of the series after a five-year hiatus, with Professors Etelka Farkas (Debrecen, Hungary) and Max Ryadnov (National Physical Laboratory, UK) as the new volume editors. There has been considerable progress in the field since the last publication in 2007, and predominantly this volume looks back over the last two year rather than the usual 12-months. However, traditional concepts are also revisited in the context of recent discoveries. Each chapter incorporates current trends of the reviewed topic and the authors' outlook of future perspectives. This is to facilitate the monitoring of the covered areas and their potentianl expansion with the inclusion of other specialist reports in subsequent volume. All chapters are compiled by leading researchers in their subject areas which offers this series as an appealing source of information for the research community in both academia and industry.
Artificial Intelligence-Driven Precision Medicine for Triple Negative Breast Cancer
Artificial Intelligence-Driven Precision Medicine for Triple-Negative Breast Cancer: Innovations and Insights in TNBC Management is a groundbreaking exploration into the transformative role of artificial intelligence in revolutionizing the management of triple-negative breast cancer (TNBC). In 19 chapters, this comprehensive guide navigates the intersection of cutting-edge technology and healthcare, offering insights that bridge the gap among medical professionals, researchers, and individuals affected by TNBC. Diving into the complexities of TNBC, this book unveils the potential of artificial intelligence (AI) in enhancing diagnostic accuracy, personalizing treatment strategies, and reshapi...
Advances in Computer Science, Engineering and Applications
The International conference series on Computer Science, Engineering & Applications (ICCSEA) aims to bring together researchers and practitioners from academia and industry to focus on understanding computer science, engineering and applications and to establish new collaborations in these areas. The Second International Conference on Computer Science, Engineering & Applications (ICCSEA-2012), held in Delhi, India, during May 25-27, 2012 attracted many local and international delegates, presenting a balanced mixture of intellect and research both from the East and from the West. Upon a strenuous peer-review process the best submissions were selected leading to an exciting, rich and a high quality technical conference program, which featured high-impact presentations in the latest developments of various areas of computer science, engineering and applications research.
Meta Learning With Medical Imaging and Health Informatics Applications
Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks' fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks.This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such...
