{"product_id":"mathematical-and-computational-studies-on-progress-prognosis-prevention-and-panacea-of-breast-cancer-9789811660795","title":"Mathematical and Computational Studies on Progress, Prognosis, Prevention and Panacea of Breast Cancer","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book studies mathematical and computational models to analyze breast cancer progress, prognosis, prevention, and panacea, using Markov chains, transient mappings, and nonlinear reaction-diffusion-type partial differential equations. It also designs mathematical models of targeted strategic treatments using Skilled Killer Drugs. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 351 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 30 March 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer Verlag, Singapore\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThis comprehensive book delves into the realm of mathematical and computational models to explore a wide range of aspects related to breast cancer. It aims to provide a comprehensive analysis of the progress, prognosis, prevention, and potential cure of this devastating disease. The book discusses the application of various techniques, including Markov chains and transient mappings, the Charlie–Simpson numerical algorithm, models represented by nonlinear reaction–diffusion-type partial differential equations, and related methodologies. Furthermore, it makes an insightful attempt to design mathematical models that can effectively analyze targeted strategic treatments, specifically focusing on Skilled Killer Drugs (SKD1 and SKD2). By employing these models, the book aims to suggest potential improvisations in future cancer treatments. This invaluable resource is designed to benefit both graduate students and researchers actively engaged in computational biology and oncology. Additionally, researchers in cancer studies and biological sciences will find this work to be highly informative and valuable.\u003cbr\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003cstrong\u003eIntroduction:\u003c\/strong\u003e\u003cbr\u003eBreast cancer is a complex and challenging medical condition that affects millions of women worldwide. With advancements in medical research and technology, there is an increasing need for effective strategies to analyze and understand the progression of breast cancer. This book aims to contribute to this endeavor by exploring the use of mathematical and computational models to analyze the various aspects of breast cancer.\u003cbr\u003e\u003cbr\u003e\u003cstrong\u003eChapter 1:\u003c\/strong\u003e\u003cbr\u003eIn this chapter, the book provides an overview of the mathematical and computational models used in breast cancer analysis. It discusses the importance of these models in understanding the progression of the disease, predicting the prognosis, and developing effective prevention and treatment strategies. The chapter also highlights the challenges associated with modeling breast cancer and the need for interdisciplinary collaboration among researchers from different fields.\u003cbr\u003e\u003cbr\u003e\u003cstrong\u003eChapter 2:\u003c\/strong\u003e\u003cbr\u003eChapter 2 focuses on the application of Markov chains and transient mappings in breast cancer analysis. It discusses the theoretical background of these models and their practical applications in modeling the progression of breast cancer cells. The chapter also explores the use of these models to predict the response of breast cancer to different treatments and to identify potential biomarkers for early detection.\u003cbr\u003e\u003cbr\u003e\u003cstrong\u003eChapter 3:\u003c\/strong\u003e\u003cbr\u003eChapter 3 delves into the use of the Charlie–Simpson numerical algorithm in breast cancer analysis. It discusses the algorithm's theoretical background and its practical applications in solving nonlinear reaction–diffusion-type partial differential equations. The chapter also highlights the importance of accurate parameter estimation in these models and the use of optimization techniques to improve the accuracy of predictions.\u003cbr\u003e\u003cbr\u003e\u003cstrong\u003eChapter 4:\u003c\/strong\u003e\u003cbr\u003eChapter 4 explores the application of models represented by nonlinear reaction–diffusion-type partial differential equations in breast cancer analysis. It discusses the theoretical background of these models and their practical applications in modeling the behavior of breast cancer cells. The chapter also explores the use of these models to predict the response of breast cancer to different treatments and to identify potential biomarkers for early detection.\u003cbr\u003e\u003cbr\u003e\u003cstrong\u003eChapter 5:\u003c\/strong\u003e\u003cbr\u003eChapter 5 focuses on the use of Skilled Killer Drugs (SKD1 and SKD2) in breast cancer treatment. It discusses the theoretical background of these drugs and their practical applications in targeting cancer cells. The chapter also explores the use of mathematical models to design targeted strategic treatments and to optimize the dosing of these drugs.\u003cbr\u003e\u003cbr\u003e\u003cstrong\u003eConclusion:\u003c\/strong\u003e\u003cbr\u003eIn conclusion, this book provides a comprehensive and up-to-date overview of the mathematical and computational models used in breast cancer analysis. It highlights the importance of these models in understanding the progression of the disease, predicting the prognosis, and developing effective prevention and treatment strategies. The book also emphasizes the need for interdisciplinary collaboration among researchers from different fields to advance our understanding of breast cancer and improve patient outcomes.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 599g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9789811660795\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2021\u003c\/p\u003e","brand":"Suhrit Dey,Charlie Dey","offers":[{"title":"Paperback \/ softback","offer_id":44188704833786,"sku":"9789811660795","price":38.43,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1682087733969_book.jpg?v=1682262973","url":"https:\/\/shulphink.com\/products\/mathematical-and-computational-studies-on-progress-prognosis-prevention-and-panacea-of-breast-cancer-9789811660795","provider":"Shulph Ink","version":"1.0","type":"link"}