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Development of machine learning techniques and artificial intelligence for the study of cancer related cachexia

Grant number: 17/17096-1
Support Opportunities:Scholarships in Brazil - Doctorate
Effective date (Start): December 01, 2017
Effective date (End): August 31, 2021
Field of knowledge:Interdisciplinary Subjects - Physics - Condensed Matter Physics
Principal Investigator:Alexandre Alarcon do Passo Suaide
Grantee:Natasha Fioretto Aguero
Host Institution: Instituto de Física (IF). Universidade de São Paulo (USP). São Paulo , SP, Brazil


Cancer patients may develop a syndrome called cachexia, in which there is a great loss of skeletal muscle mass and it is linked to a pessimistic prognosis. One hypothesis is that epigenetic factors, such as physical conditioning, could influence the evolution of this syndrome. The cancer metabolism group of the Institute of Biomedical Sciences of USP, headed by Prof. Dr. Marília Seelaender, has performed several experiments to test this assertion, from clinical examinations to DNA sequencing of human patients. The massive amount of the obtained data makes it necessary to apply computational methods for statistical analysis. In this project, machine learning techniques will be implemented in order to identify markers that may aid in the early diagnosis of cachexia in cancer patients, in addition to identifying possible epigenetic factors that may influence the prognosis of the disease.

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