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Draft:Mathematical oncology

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  • Comment: This draft seems to be largely written with a large language model, which is generally not helpful for creating Wikipedia article content. Please rewrite this in your own words. Let me know if you have any questions! (please Reply to icon mention me on reply; thanks!) —TechnoSquirrel69 (sigh) 01:37, 22 September 2024 (UTC)

Mathematical Oncology is a specialized branch of oncology.:[1] in which mathematical methods, including modeling[2] and simulations,[3] are applied to the study of cancer[4] growth, progression, and treatment.[5] Researchers develop models that describe tumor dynamics, treatment responses, and potential outcomes, supporting the development of more effective treatment strategies.[6] Simulation of cancer behavior potentially reduces the need for early-phase experimental trials.[7][8]

Mathematical oncology employs both deterministic[9] and stochastic[10] models to simulate tumor behavior. These models frequently rely on ordinary differential equations (ODEs)[11] and partial differential equations (PDEs)[12] to represent tumor growth, angiogenesis,[13] metastasis development,[14] and treatment responses.

Control theory[15] and optimization[16] are applied to treatment planning in cancer therapies, particularly in radiotherapy[17] and chemotherapy.[18] By optimizing dose schedules and timing, mathematical oncology aims to maximize therapeutic efficacy while minimizing adverse effects.[19]

Statistical methods[20] can be important for understanding cancer progression, analyzing treatment outcomes, and identifying significant trends in large data sets.[21] Recent advances in artificial intelligence (AI)[22] and machine learning[23] have further impacted the field. AI algorithms[24] can process larger amounts of patient data and identify patterns that may predict individual responses to treatment, personalizing therapeutic strategies.[25]

Recent advancements in computational techniques, particularly in AI, have significantly increased progress in mathematical oncology.[26] AI allows researchers to predict the behavior of individual cells with greater accuracy by integrating diverse types of patient data. AI-driven models can also identify mathematical equations that more precisely reflect tumor growth dynamics, helping researchers uncover relationships between various biological factors more quickly.[27] [28]

References

[edit]

Moffitt Cancer Center's Integrated Mathematical Oncology Program: https://www.moffitt.org/research-science/divisions-and-departments/quantitative-science/integrated-mathematical-oncology/

City of Hope's Division of Mathematical Oncology: https://www.cityofhope.org/research/mathematical-oncology

Society for Mathematical Biology: https://www.smb.org/

Mathematical Oncology Blog: https://mathematical-oncology.org/

  1. ^ "Oncology".
  2. ^ "Mathematical model".
  3. ^ "Simulation".
  4. ^ "Cancer".
  5. ^ Altrock, P., Liu, L. & Michor, F. The mathematics of cancer: integrating quantitative models. Nat Rev Cancer 15, 730–745 (2015). https://doi.org/10.1038/nrc4029
  6. ^ Gibin G. Powathil, Maciej Swat, Mark A.J. Chaplain, Systems oncology: Towards patient-specific treatment regimes informed by multiscale mathematical modeling, Seminars in Cancer Biology, Volume 30, 2015, Pages 13-20, ISSN 1044-579X, https://doi.org/10.1016/j.semcancer.2014.02.003.
  7. ^ "Phases of clinical research".
  8. ^ Chambers RB. The role of mathematical modeling in medical research: "research without patients?". Ochsner J. 2000 Oct;2(4):218-23. PMID: 21765699; PMCID: PMC3117507
  9. ^ "Deterministic system".
  10. ^ "Stochastic process".
  11. ^ "Ordinary differential equation".
  12. ^ "Partial differential equation".
  13. ^ "Angiogenesis".
  14. ^ "Metastasis".
  15. ^ "Control theory".
  16. ^ https://en.wikipedia.org/wiki/Mathematical_optimiza,tion
  17. ^ "Radiation therapy".
  18. ^ https://en.wikipedia.org/wiki/Chemotherap
  19. ^ Optimizing the future: how mathematical models inform treatment schedules for cancer Mathur, Deepti et al. Trends in Cancer, Volume 8, Issue 6, 506 - 516
  20. ^ "Statistical Methods in Medical Research".
  21. ^ "Data set".
  22. ^ "Artificial intelligence".
  23. ^ "Machine learning".
  24. ^ "Artificial intelligence in healthcare".
  25. ^ Janina Hesse, Nina Nelson, Angela Relógio, Shaping the future of precision oncology: Integrating circadian medicine and mathematical models for personalized cancer treatment, Current Opinion in Systems Biology, Volume 37,2024,100506,ISSN 2452-3100, https://doi.org/10.1016/j.coisb.2024.100506
  26. ^ Shimizu H, Nakayama KI. Artificial intelligence in oncology. Cancer Sci. 2020; 111: 1452–1460. https://doi.org/10.1111/cas.14377
  27. ^ El Naqa, I., Karolak, A., Luo, Y. et al. Translation of AI into oncology clinical practice. Oncogene 42, 3089–3097 (2023). https://doi.org/10.1038/s41388-023-02826-z
  28. ^ "AI and Cancer - NCI". 30 May 2024.
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