Systems Cancer

This book explores drug delivery strategies for therapeutic products including vitamins, emphasizing the delivery of live cell therapies. It also highlights nanostructured systems tailored for smart drug delivery and theranostic medicines, showcasing promising advancements in this emerging field.

Systems Biology in Cancer Research and Drug Discovery provides a unique collection of chapters, by world-class researchers, describing the use of integrated systems biology and network modeling in the cancer field where traditional tools have failed to deliver expected promise.

This book explores drug delivery strategies for therapeutic products including vitamins, emphasizing the delivery of live cell therapies. It also highlights nanostructured systems tailored for smart drug delivery and theranostic medicines, showcasing promising advancements in this emerging field.

This book reviews the current applications and future prospects of nanomaterials in cancer diagnostics and therapy. Nanomaterials have recently emerged as a remarkable and promising tool for cancer therapy and diagnosis, due to their broad range of intrinsic molecular properties. To overcome the current limitations of nanoparticles in drug delivery systems, attempts have been made to synthesize nanoparticles from biological materials for targeted cancer therapy.

This book presents high-quality research papers presented at the International Conference on Soft Computing for Intelligent Systems (SCIS 2020), held during 18–20 December 2020 at University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India. The book encompasses all branches of artificial intelligence, computational sciences and machine learning which is based on computation at some level such as AI-based Internet of things, sensor networks, robotics, intelligent diabetic retinopathy, intelligent cancer genes analysis using computer vision, evolutionary algorithms, fuzzy systems, medical automatic identification intelligence system and applications in agriculture, health care, smart grid and instrumentation systems.

This book’s aim is to study the mathematical and computational models to analyze the progress, prognosis, prevention, and panacea of breast cancer. The book discusses application of Markov chains and transient mappings, Charlie–Simpson numerical algorithm, models represented by nonlinear reaction–diffusion-type partial differential equations, and related techniques. The book also attempts to design mathematical model of targeted strategic treatments by using Skilled Killer Drugs (SKD1 and SKD2) to suggest the improvisation of future cancer treatments. Both graduate students and researchers of computational biology and oncologists will benefit by studying this book. Researchers of cancer studies and biological sciences will also find this work helpful.

The worldwide cancer burden will double over the next two decades, with the number of new cancer diagnoses increasing in all regions of the world. However, it is estimated that around 40% of all cancers are preventable through the appropriate application of existing epidemiological and public health knowledge, and with further research this proportion will increase considerably. This edited volume explores the role of place in cancer prevention and how geospatial tools can be used to support this globally important goal. Its chapters detail many aspects of the application of geospatial science to cancer control, including quantifying exposure to environmental carcinogens, access to screening services, the importance of partnership building, and more through a variety of geographically diverse case studies. The book also offers background on geospatial modeling tools and methods for adding spatial analysis to cancer surveillance systems. The book is rooted firmly in the notion that geography significantly influences the accumulation of cancer risks (at the individual and community level) that are modifiable through policy, regulatory, and behavioral changes.