Tumor Cell RMAE Comparison for DDPG Chemotherapy Framework

A 5.5 KB Excel file contains data comparing RMAE (Relative Mean Absolute Error) in tumor cells under a deep reinforcement learning framework. The dataset, authored by Wenlang Zhu, was last updated in April 2026 and supports a proposed DDPG algorithm for personalized chemotherapy regulation.

Use Cases

• Benchmark the RMAE metric of a DDPG agent against other control methods in simulated tumor environments.
• Analyze the relationship between drug concentration control inputs and tumor cell population dynamics.
• Validate the stability of a chemotherapy dosing strategy under simulated physiological noise and uncertainty.

Strengths

• Data supports a published methodological framework for chemotherapy optimization.
• Available under a permissive CC-BY-4.0 license for reuse.

Limitations

• Dataset is very small at 5.5 KB, indicating limited scope and likely a summary of results rather than raw simulation data.
• Specific row count, column names, and sample data are unavailable, limiting direct analysis.

Provenance

Source

Wenlang Zhu via figshare.

Collection Method

Generated from simulations of a nonlinear dynamic system modeling tumor microenvironment interactions.

Freshness

Last updated in April 2026, indicating it is forward-dated and likely represents planned or simulated future work.