{"product_id":"computational-mathematics-modeling-in-cancer-analysis-first-international-workshop-cmmca-2022-held-in-conjunction-with-miccai-2022-singapore-september-18-2022-proceedings-9783031172656","title":"Computational Mathematics Modeling in Cancer Analysis: First International Workshop, CMMCA 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThe book summarizes the proceedings of the First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022), held virtually in September 2022, which focused on identifying new techniques and applications in cancer data analysis. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 160 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 20 September 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThe First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022) was held in Singapore in September 2022, in conjunction with MICCAI 2022, due to the COVID-19 pandemic restrictions. The workshop aimed to identify new cutting-edge techniques and their applications in cancer data analysis, addressing trends and challenges in theoretical, computational, and applied aspects of mathematics in cancer data analysis.\u003cbr\u003e\u003cbr\u003eDALI 2022 accepted 15 papers out of 16 submissions, with a significant focus on exploring innovative approaches and their implementations in cancer data analysis. The workshop brought together experts from various fields, including mathematics, computer science, statistics, and medicine, to discuss and advance the state-of-the-art in this rapidly evolving domain.\u003cbr\u003e\u003cbr\u003eThe papers presented at CMMCA2022 covered a wide range of topics, including cancer genomics, machine learning, statistical modeling, and computational biology. Some of the key themes explored included the development of novel algorithms for analyzing large cancer datasets, the integration of multi-modal data for better cancer diagnosis and treatment, and the application of mathematical models to understand the biological mechanisms underlying cancer development and progression.\u003cbr\u003e\u003cbr\u003eThe workshop also featured interactive sessions, panel discussions, and keynote lectures by renowned researchers in the field. These sessions provided opportunities for participants to exchange ideas, collaborate, and learn from each other, fostering a vibrant research community dedicated to advancing computational mathematics modeling in cancer analysis.\u003cbr\u003e\u003cbr\u003eOverall, CMMCA2022 was a successful event that highlighted the importance of interdisciplinary collaboration in addressing complex challenges in cancer data analysis. The workshop's proceedings will contribute to the ongoing development of this field and provide valuable insights for researchers, practitioners, and policymakers alike.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 273g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031172656\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44289567555834,"sku":"9783031172656","price":42.69,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_69ed5335-2b61-4821-a0b3-5b6c4b5263b8.jpg?v=1687281947","url":"https:\/\/shulphink.com\/products\/computational-mathematics-modeling-in-cancer-analysis-first-international-workshop-cmmca-2022-held-in-conjunction-with-miccai-2022-singapore-september-18-2022-proceedings-9783031172656","provider":"Shulph Ink","version":"1.0","type":"link"}