Banca de QUALIFICAÇÃO: RAPHAEL JOSÉ RODRIGUES TORRES

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : RAPHAEL JOSÉ RODRIGUES TORRES
DATE: 27/03/2023
TIME: 14:00
LOCAL: Google Meet, meet.google.com/yqk-yoka-cbp
TITLE:

Intelligent computational system to support the clinical diagnosis of breast cancer from mammograms.

KEY WORDS:

breast cancer, machine learning, bioinformatics, convolutional artificial neural networks.

PAGES: 30
BIG AREA: Ciências Biológicas
AREA: Biologia Geral
SUMMARY:

Breast cancer has the second highest incidence of cancer among women. Early diagnosis is essential for determining treatment and chance of cure. Among the various diagnostic methods, periodic mammography is the gold standard for identifying tumors, but it depends on the visual interpretation of the medical team involved. A failure to identify tumors has serious implications for the patient, in addition to possibly incurring in longer and more expensive tests and treatments. Therefore, the development of computational tools to support medical decisions is essential to improve the diagnostic process. The objective of this project is the construction of an intelligent, safe and flexible computational system to support the clinical diagnosis of breast cancer. As a first step, a database will be organized from the mammography exams already performed in the Liga Contra o Câncer. Next, a convolutional artificial neural network will be developed for the automatic classification of breast tumors. Finally, federated learning tools will be adapted so that the developed system has greater security in the use of decentralized medical data, and greater performance and robustness to new cases, in line with the Lei Geral de Proteção de Dados (2018).

COMMITTEE MEMBERS:
Externa ao Programa - 1885001 - ANNA GISELLE CAMARA DANTAS RIBEIRO RODRIGUES - nullInterno - 2276280 - CESAR RENNO COSTA
Presidente - 3083298 - RENAN CIPRIANO MOIOLI