Reprint

Artificial Intelligence in Cancer, Biology and Oncology

Edited by
May 2024
314 pages
  • ISBN978-3-7258-1111-3 (Hardback)
  • ISBN978-3-7258-1112-0 (PDF)

This is a Reprint of the Topic that was published in

Biology & Life Sciences
Medicine & Pharmacology
Public Health & Healthcare
Summary

This reprint covers some significant impacts in recent research, in both the private and public sectors of cancer biology and oncology, in which artificial intelligence (AI) and machine learning are significant. This reprint is also a collection of forty different complex and challenging problems arranged in five groups which are focused on AI in diagnosis and therapy: AI in prognosis, grading and prediction; AI in clinical image analysis; AI models for pathological diagnosis; ML and statistical models for molecular cancer diagnostics and genetics; and AI in cancer triage, risk stratification, and screening. All necessary concepts, solutions, methodologies, and references are supplied, except for some fundamental knowledge that is well known in the general fields of AI and cancer, biology, and oncology. The readers may therefore gain the main concepts of each chapter, little need to refer to the concepts of the other chapters and references. The readers may hence start to read one or more chapters of the reprint according to their own interests.

Format
  • Hardback
License and Copyright
© 2024 by the authors; CC BY-NC-ND license
Keywords
artificial intelligence; machine learning; bioinformatics; modeling complex biological systems; computational cancer biology; computational drug discovery; radiology; radiation therapy (oncology); cancer diagnosis and cancer therapy