Fractional order breast cancer model with therapy, prevention diagnosis and optimal control based on real data.

Shaimaa A M Abdelmohsen, Haifa A Alyousef, Sayed Saifullah

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Shaimaa A M AbdelmohsenDepartment of Physics, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.

Haifa A AlyousefDepartment of Physics, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia. haalyousef@pnu.edu.sa.

Sayed SaifullahDepartment of Mathematics and Physics, University of Campania "Luigi Vanvitelli", 81100, Caserta, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is one of the most perilous diseases worldwide, often incurable if not diagnosed in its early stages. Among cancers, breast cancer ranks as the second most lethal, particularly affecting women and contributing to a significant number of fatalities. This work analyzes the breast cancer model in the fractional scenario by incorporating the therapy and prevention diagnosis. The model is subjected to theoretical and numerical investigations to explore the dynamics and predictions of the disease. Furthermore, optimal disease control is presented along with a sensitivity analysis of model parameters. Furthermore, the obtained results are compared with the real data with varying fractional orders, revealing that most of the data points coincide with the fractional order 0.98.

Indexed as

Breast NeoplasmsFemaleHumansModels, TheoreticalBreast cancer modelDrug therapyFractional operatorOptimal controlSensitivity analysis

Identifiers

PMID40685391

DOI10.1038/s41598-025-03357-1

PMCPMC12277451

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LicenceCC BY-NC-ND

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.