Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer (2020)
- Authors:
- Autor USP: MITROWSKY, RAFAEL ANDRES ROSALES - FFCLRP
- Unidade: FFCLRP
- DOI: 10.3390/cancers12123687
- Subjects: BIOMARCADORES; NEOPLASIAS; DNA; APRENDIZADO COMPUTACIONAL; TERAPÊUTICA MÉDICA; ALGORITMOS; CARCINOGÊNESE; IMUNOTERAPIA; RECOMBINAÇÃO GENÉTICA
- Keywords: Digital pathology; Deep learning; Mutational signature; Biomarker; DNA repair deficiency
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
ABNT
VALIERIS, Renan et al. Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer. Cancers, v. 12, n. 12, p. 1-12, 2020Tradução . . Disponível em: https://doi.org/10.3390/cancers12123687. Acesso em: 04 ago. 2025. -
APA
Valieris, R., Amaro, L., Osório, C. A. B. de T., Bueno, A. P., Mitrowsky, R. A. R., Carraro, D. M., et al. (2020). Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer. Cancers, 12( 12), 1-12. doi:10.3390/cancers12123687 -
NLM
Valieris R, Amaro L, Osório CAB de T, Bueno AP, Mitrowsky RAR, Carraro DM, Nunes DN, Dias-Neto E, Silva IT da. Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer [Internet]. Cancers. 2020 ; 12( 12): 1-12.[citado 2025 ago. 04 ] Available from: https://doi.org/10.3390/cancers12123687 -
Vancouver
Valieris R, Amaro L, Osório CAB de T, Bueno AP, Mitrowsky RAR, Carraro DM, Nunes DN, Dias-Neto E, Silva IT da. Deep learning predicts underlying features on pathology images with therapeutic relevance for breast and gastric cancer [Internet]. Cancers. 2020 ; 12( 12): 1-12.[citado 2025 ago. 04 ] Available from: https://doi.org/10.3390/cancers12123687 - Cálculo estocástico e aplicações em finanças
- A série de Hardy-Ramanujan-Rademacher para o número de participações de um inteiro positivo
- Interacting vertex reinforced random walks on complete sub-graphs
- Bounding the speed of harris chains via Griffeath's maximal coupling
- HIV-1 integration landscape during latent and active infection
- Relating mutational signature exposures to clinical data in cancers via signeR 2.0
- Identification of chromosomal translocation hotspots via scan statistics
- Repelling random walks in complete graphs
- Topological dynamics of piecewise λ-affine maps
- Mutational signatures driven by epigenetic determinants enable the stratification of patients with gastric cancer for therapeutic intervention
Informações sobre o DOI: 10.3390/cancers12123687 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
003021279.pdf | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
