Computational Intelligence in Oncology: Applications in Diagnosis, Prognosis and Therapeutics of Cancers

This  book encapsulates recent applications of CI methods in the field of  computational oncology, especially cancer diagnosis, prognosis, and its  optimized therapeutics.

The cancer has been known as a  heterogeneous disease categorized in several different subtypes.  According to WHO’s recent report, cancer is a leading cause of death  worldwide, accounting for over 10 million deaths in the year 2020.  Therefore, its early diagnosis, prognosis, and classification to a  subtype have become necessary as it facilitates the subsequent clinical  management and therapeutics plan. Computational intelligence (CI)  methods, including artificial neural networks (ANNs), fuzzy logic,  evolutionary computations, various machine learning and deep learning,  and nature-inspired algorithms, have been widely utilized in various  aspects of oncology research, viz. diagnosis, prognosis, therapeutics,  and optimized clinical management.

Appreciable progress has been  made toward the understanding the hallmarks of cancer development,  progression, and its effective therapeutics. However, notwithstanding  the extrinsic and intrinsic factors which lead to drastic increment in  incidence cases, the detection, diagnosis, prognosis, and therapeutics  remain an apex challenge for the medical fraternity. With the advent in  CI-based approaches, including nature-inspired techniques, and  availability of clinical data from various high-throughput experiments,  medical consultants, researchers, and oncologists have seen a hope to  devise and employ CI in various aspects of oncology. The main aim of the  book is to occupy state-of-the-art applications of CI methods which  have been derived from core computer sciences to back medical oncology.  This edited book covers artificial neural networks, fuzzy logic and  fuzzy inference systems, evolutionary algorithms, various  nature-inspired algorithms, and hybrid intelligent systems which are  widely appreciated for the diagnosis, prognosis, and optimization of  therapeutics of various cancers. Besides, this book also covers  multi-omics exploration, gene expression analysis, gene signature  identification of cancers, genomic characterization of tumors,  anti-cancer drug design and discovery, drug response prediction by means  of CI, and applications of IoT, IoMT, and blockchain technology in  cancer research.