Comparative oncology of male and female breast cancer: diagnostic paradigms and machine learning approaches in treatment
Résumé fourni par la source
Breast cancer is associated mostly with women; however, breast cancer also appears in men, which dictates the need to know about gender-specific differences in the pathology and treatment. Male breast cancer constitutes less than 1 % of all cases and is usually diagnosed when the patient is older, with bigger tumors and at later stages than breast cancer in women. The most widespread subtype in both genders is invasive ductal carcinoma. The effect of hormone receptor positivity is very prominent in the treatment of men, and the risk factors include the BRCA2 mutations and the hormonal imbalance. The management approach, such as surgery, chemotherapy, radiotherapy, and hormonal therapy, is like that of women, and it may vary in treatment effectiveness because of hormonal and biological differences. The prognostic data in males are scarce, with generally worse outcomes, most likely because of delayed diagnosis and low rates of clinical trial representation. Men with breast cancer also face special psychosocial obstacles with regard to stigma and support. The use of artificial intelligence (AI) and machine learning are emerging options that have the potential to improve detectability and personalized treatment in both genders. The current review draws similarities between breast cancer in males and females to promote gender-specific interventions and better outcomes.
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Contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Comparative oncology of male and female breast cancer: diagnostic paradigms and machine learning approaches in treatment
- Date Crossref
- 01/05/2026
- Éditeur
- Walter de Gruyter GmbH
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.
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