Applying Chaos Theory and Image Analysis for the Assessment and Prognosis of Severe Carcinomas

Science / Computer Science

The interactions between biological structures are known to follow a complex and highly non-linear dynamic, making chaos theory a fitting approach for their study. This project proposes the application of chaos theory to explore the relationship between the cellular morphology of aggressive cancer types, such as certain lung carcinomas, and their biological development. The dynamics of these interactions will be analyzed using microscopic images of the affected tissue. This approach offers a simpler and more flexible model compared to traditional physical models. The project aims to answer the following questions: 1) How do the non-linear characteristics of these images correlate with the risk of developing cancer? 2) How does the progression of these images over time relate to the disease’s evolution and the impact of administered treatments? 3) The anticipated results from this study could enhance diagnostic procedures and inform the development of therapies that improve patient survival rates and quality of life.

Amount invested

Grant 2019: R$ 50.000,00
  • Topics
  • câncer
  • Chaos theory
  • therapies