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Cancer Control Algorithm.
Sunil Kumar Kashyap1, Birendra Kumar Sharma2, Amitabh Banerjee2
1Vellore Institute of Technology University, Vellore, Tamil Nadu-632014, India.
This study introduces a Cancer Control Algorithm to manage cancer cell growth by minimizing its rate. The research aims to structure chaotic cancer development for future cancer research and treatment strategies.
Area of Science:
- Oncology
- Mathematical Biology
- Computational Medicine
Background:
- The Warburg effect describes a metabolic shift in cancer cells, defining their center.
- Understanding cancer cell proliferation is crucial for developing effective treatments.
- Existing models often focus on metabolic aspects rather than direct growth control.
Purpose of the Study:
- To develop a computational method for controlling cancer cell growth.
- To minimize the rate of cancer cell proliferation using optimization programming.
- To provide a structured model for chaotic cancer development.
Main Methods:
- Analysis of cancer cell growth using optimization programming.
- Development and application of a novel Cancer Control Algorithm.
- Modeling cancer growth as a controlled circular expansion.
Main Results:
- The proposed algorithm effectively minimizes the rate of cancer cell growth.
- The Cancer Control Algorithm successfully controls the increasing radius of cancer cell clusters.
- Chaotic cancer cell growth patterns were successfully structured for further analysis.
Conclusions:
- Controlling cancer cell growth rate is achievable through computational algorithms.
- The Cancer Control Algorithm offers a novel approach to cancer management.
- This research provides a foundation for developing targeted cancer therapies based on growth control.
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