Experimental Parameters for Fractional-Order Breast Cancer Treatment Models

A computational study by Irshad Sikandar Jamadar, last updated in May 2026, presents parameters for modeling breast cancer treatment dynamics. The dataset includes 11 experimental parameters used in a fractional-order framework to simulate tumor growth, immune response, and resistance across five treatment protocols and four patient populations. It is shared on figshare under a CC-BY-4.0 license.

Use Cases

• Calibrating fractional-order differential equation models based on the described parameter values.
• Comparing treatment protocol efficacy (Continuous, Adaptive) across different patient populations.
• Performing sensitivity analysis on model parameters, such as immune cytotoxic killing rate.
• Investigating the impact of memory effects in biological systems on treatment predictions.

Strengths

• Includes specific efficacy results, such as a maximum benefit of 32.38 for younger patients under a defined protocol.
• Explicitly compares fractional-order (0.75 to 1.0) and integer-order models, quantifying context-specific improvements up to 3.68%.
• Parameters are defined for five distinct treatment protocols and four patient population types.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small at 5.5 KB, indicating limited scope.

Provenance

Source

figshare

Collection Method

Likely generated from computational simulations of a fractional-order mathematical model.

Freshness

Last updated 2026-05-14 17:38:11; freshness should be verified.