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Related Concept Videos

Mouse Models of Cancer Study02:43

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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Updated: Sep 9, 2025

Author Spotlight: Computing the Effects of a Local Radiofrequency Hyperthermia Intervention on Tumor Biomechanics
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Computational modeling and simulation in oncology.

Christian Baumgartner1

  • 1Department of Computer Science and Biomedical Engineering, Institute of Health Care Engineering with European Testing Center of Medical Devices, Graz University of Technology, Graz, Austria.

Clinical and Translational Medicine
|September 5, 2025
PubMed
Summary
This summary is machine-generated.

Computational modeling and simulation are advancing cancer research and treatment. These computational tools, including AI and digital twins, are paving the way for precision medicine and personalized cancer care.

Keywords:
cancercomputational modelingdigital twinsin silico trialsmultiscale modelingoncologyprecision medicine

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Area of Science:

  • Oncology
  • Computational Biology
  • Bioinformatics

Background:

  • Computational modeling and simulation are crucial in understanding cancer complexity.
  • These methods bridge biological research, data science, and clinical oncology.
  • Advances are essential for informing therapeutic development in cancer.

Discussion:

  • This special issue highlights multiscale modeling, AI-driven systems, digital twins, and in silico trials.
  • These computational tools demonstrate evolving potential for innovation in oncology.
  • The integration of computational approaches supports the transition from bench to bedside.

Key Insights:

  • Multiscale modeling offers deeper insights into cancer biology.
  • Artificial intelligence (AI) systems are enhancing predictive capabilities in oncology.
  • Digital twins and in silico trials provide powerful platforms for testing therapeutic strategies.

Outlook:

  • Future cancer care will be guided by integrative and predictive modeling approaches.
  • Precision medicine will be increasingly informed by computational simulations.
  • Adaptive therapies and personalized diagnostics are expected to benefit from these advancements.