BRCA1/2 pathogenic mutations significantly increase the risk of developing breast cancer at a younger age and with a higher grade, especially within the female population. This study focuses on patients with BRCA1/2 pathogenic mutations in order to: 1) identify the main risk factors for developing cancer at a younger age; 2) determine the key risk factors for the development of higher-grade breast cancers; and 3) classify genetic sequences, obtained through genetic testing, as either pathogenic or benign using interpretable deep learning models.

BRCA1/2 pathogenic mutations significantly increase the risk of developing breast cancer at a younger age and with a higher grade, especially within the female population. This study focuses on patients with BRCA1/2 pathogenic mutations in order to: 1) identify the main risk factors for developing cancer at a younger age; 2) determine the key risk factors for the development of higher-grade breast cancers; and 3) classify genetic sequences, obtained through genetic testing, as either pathogenic or benign using interpretable deep learning models.

Understanding Pathogenic Mutations BRCA1/2: Interpretation and Classification

TOMASELLI, FRANCESCO
2023/2024

Abstract

BRCA1/2 pathogenic mutations significantly increase the risk of developing breast cancer at a younger age and with a higher grade, especially within the female population. This study focuses on patients with BRCA1/2 pathogenic mutations in order to: 1) identify the main risk factors for developing cancer at a younger age; 2) determine the key risk factors for the development of higher-grade breast cancers; and 3) classify genetic sequences, obtained through genetic testing, as either pathogenic or benign using interpretable deep learning models.
2023
Understanding Pathogenic Mutations BRCA1/2: Interpretation and Classification
BRCA1/2 pathogenic mutations significantly increase the risk of developing breast cancer at a younger age and with a higher grade, especially within the female population. This study focuses on patients with BRCA1/2 pathogenic mutations in order to: 1) identify the main risk factors for developing cancer at a younger age; 2) determine the key risk factors for the development of higher-grade breast cancers; and 3) classify genetic sequences, obtained through genetic testing, as either pathogenic or benign using interpretable deep learning models.
Statistics
Deep Learning
Pathogenic Mutations
BRCA1/2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/80904