Skip to main navigation Skip to search Skip to main content

Computational Intelligence in Cancer Diagnosis: Progress and Challenges

  • Janmenjoy Nayak
  • , Danilo Pelusi
  • , Bighnaraj Naik
  • , Manohar Mishra
  • , Khan Muhammad
  • , David Al-Dabass
  • Maharaja Sriram Chandra Bhanja Deo University
  • University of Teramo
  • Siksha ‘O’ Anusandhan University
  • Nottingham Trent University

Research output: Book/ReportBookpeer-review

Abstract

Computational Intelligence in Cancer Diagnosis: Progress and Challenges provides insights into the current strength and weaknesses of different applications and research findings on computational intelligence in cancer research. The book improves the exchange of ideas and coherence among various computational intelligence methods and enhances the relevance and exploitation of application areas for both experienced and novice end-users. Topics discussed include neural networks, fuzzy logic, connectionist systems, genetic algorithms, evolutionary computation, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. The book's chapters are written by international experts from both cancer research, oncology and computational sides to cover different aspects and make it comprehensible for readers with no background on informatics.

Original languageEnglish
PublisherElsevier
Number of pages395
ISBN (Electronic)9780323852401
DOIs
StatePublished - 1 Jan 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Fingerprint

Dive into the research topics of 'Computational Intelligence in Cancer Diagnosis: Progress and Challenges'. Together they form a unique fingerprint.

Cite this