{"product_id":"computational-intelligence-in-cancer-diagnosis-progress-and-challenges-9780323852401","title":"Computational Intelligence in Cancer Diagnosis: Progress and Challenges","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eComputational Intelligence in Cancer Diagnosis: Progress and Challenges explores the strengths and weaknesses of various computational intelligence methods in cancer research, improving the exchange of ideas and coherence among different approaches. The book covers neural networks, fuzzy logic, genetic algorithms, evolutionary computation, and more, written by international experts. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 420 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 28 April 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Elsevier Science \u0026amp; Technology\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eComputational Intelligence in Cancer Diagnosis: Progress and Challenges delves into the current state of various computational intelligence applications and research findings in cancer research. By fostering a better exchange of ideas and enhancing coherence among different computational intelligence methods, the book aims to increase the relevance and practical exploitation of these techniques for both experienced and novice end-users. The book covers a wide range of topics, including neural networks, fuzzy logic, connectionist systems, genetic algorithms, evolutionary computation, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Each chapter is authored by international experts from both cancer research and computational fields, ensuring that the content is comprehensive and accessible to readers with no prior background in informatics.\u003cbr\u003e\u003cbr\u003eThe book serves as a valuable resource for researchers, practitioners, and students in the field of cancer diagnosis, providing insights into the latest advancements and challenges in computational intelligence. It offers a comprehensive overview of the various methods and techniques employed in cancer research, enabling readers to better understand and apply these tools to improve patient outcomes.\u003cbr\u003e\u003cbr\u003eOne of the key strengths of the book is its interdisciplinary approach, bringing together experts from different domains to explore the intersection of cancer research and computational intelligence. This collaboration enhances the understanding of complex cancer-related problems and facilitates the development of more effective and personalized treatment strategies.\u003cbr\u003e\u003cbr\u003eAnother notable aspect of the book is its emphasis on practical applications. The chapters provide real-world examples and case studies that demonstrate the practical benefits of computational intelligence in cancer diagnosis. These examples help readers to connect the theoretical concepts with practical implementations and inspire them to explore further the potential of these techniques in their own research and clinical practice.\u003cbr\u003e\u003cbr\u003eHowever, despite the significant progress made in computational intelligence in cancer diagnosis, the book also highlights several challenges that need to be addressed. One of the challenges is the lack of standardized data formats and protocols, which makes it difficult to integrate and analyze data from different sources. This challenge hinders the development of accurate and reproducible computational models and limits the ability to compare and evaluate different approaches.\u003cbr\u003e\u003cbr\u003eAnother challenge is the complexity of cancer-related data, which often includes high-dimensional features, heterogeneous populations, and temporal dependencies. This complexity poses significant challenges for computational intelligence methods, which typically rely on simplified models and assumptions.\u003cbr\u003e\u003cbr\u003eTo address these challenges, the book suggests several strategies. One strategy is the development of standardized data formats and protocols that enable seamless integration and analysis of data from different sources. This would facilitate the development of more accurate and comprehensive computational models and enable researchers to compare and evaluate different approaches more effectively.\u003cbr\u003e\u003cbr\u003eAnother strategy is the development of more sophisticated computational intelligence methods that can handle the complexity of cancer-related data. This includes methods such as deep learning, machine learning, and graph analytics, which have shown promising results in other fields but have yet to be fully explored in cancer diagnosis.\u003cbr\u003e\u003cbr\u003eIn conclusion, Computational Intelligence in Cancer Diagnosis: Progress and Challenges is a comprehensive and timely book that provides valuable insights into the current strength and weaknesses of different computational intelligence applications and research findings in cancer research. By fostering a better exchange of ideas and enhancing coherence among different computational intelligence methods, the book aims to increase the relevance and practical exploitation of these techniques for both experienced and novice end-users. The book's interdisciplinary approach, emphasis on practical applications, and discussion of challenges and strategies make it a valuable resource for researchers, practitioners, and students in the field of cancer diagnosis. As computational intelligence continues to evolve and play an increasingly important role in cancer research, this book will undoubtedly remain a cornerstone for future advancements in this field.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 834g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 191 x 235 x 24 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9780323852401\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44201327558906,"sku":"9780323852401","price":123.17,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1682683838562_book.jpg?v=1682792904","url":"https:\/\/shulphink.com\/products\/computational-intelligence-in-cancer-diagnosis-progress-and-challenges-9780323852401","provider":"Shulph Ink","version":"1.0","type":"link"}