Extracting morphological features to differentiate histological subtypes of lung adenocarcinoma: an attempt to improve diagnostic accuracy by using a deep learning algorithm (2021)
- Authors:
- Autor USP: FABRO, ALEXANDRE TODOROVIC - FMRP
- Unidade: FMRP
- DOI: 10.1038/s41379-021-00772-3
- Subjects: NEOPLASIAS PULMONARES; ADENOCARCINOMA; PULMÃO; ALGORITMOS; NEOPLASIAS PULMONARES
- Language: Inglês
- Imprenta:
- Source:
- Título: Modern Pathology
- ISSN: 0893-3952
- Volume/Número/Paginação/Ano: v. 34, Suppl. 2, p. 1116-1117, abst. 934, 2021
- Conference titles: Annual Meeting USCAP
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: bronze
- Licença: publisher-specific-oa
-
ABNT
LAMI, Kris et al. Extracting morphological features to differentiate histological subtypes of lung adenocarcinoma: an attempt to improve diagnostic accuracy by using a deep learning algorithm. Modern Pathology. Amsterdam: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1038/s41379-021-00772-3. Acesso em: 27 dez. 2025. , 2021 -
APA
Lami, K., Attanoos, R., Beasley, M. B., Berezowska, S., Brcic, L., Cavazza, A., et al. (2021). Extracting morphological features to differentiate histological subtypes of lung adenocarcinoma: an attempt to improve diagnostic accuracy by using a deep learning algorithm. Modern Pathology. Amsterdam: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1038/s41379-021-00772-3 -
NLM
Lami K, Attanoos R, Beasley MB, Berezowska S, Brcic L, Cavazza A, English J, Fabro AT, Ishida K, Kashima Y, Larsen B. Extracting morphological features to differentiate histological subtypes of lung adenocarcinoma: an attempt to improve diagnostic accuracy by using a deep learning algorithm [Internet]. Modern Pathology. 2021 ; 34 1116-1117.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1038/s41379-021-00772-3 -
Vancouver
Lami K, Attanoos R, Beasley MB, Berezowska S, Brcic L, Cavazza A, English J, Fabro AT, Ishida K, Kashima Y, Larsen B. Extracting morphological features to differentiate histological subtypes of lung adenocarcinoma: an attempt to improve diagnostic accuracy by using a deep learning algorithm [Internet]. Modern Pathology. 2021 ; 34 1116-1117.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1038/s41379-021-00772-3 - Taenia crassiceps injection into the subarachnoid space of rats simulates radiological and morphological features of racemose neurocysticercosis
- The effects of intratendinous injections of corticosteroid into achilles tendon: an experimental randomized study in a rabbit model
- The role of glucose metabolism and insulin resistance in cardiac remodelling induced by cigarette smoke exposure
- Recovery of cardiac remodeling and dysmetabolism by pancreatic islet injury improvement in diabetic rats after yacon leaf extract treatment
- Paracoccidioidomycosis: current perspectives from Brazil
- Green tea (Camellia sinensis) extract increased topoisomerase II β, improved antioxidant defense, and attenuated cardiac remodeling in an acute doxorubicin toxicity model
- Short-term changes after corticosteroid injections into the normal tendons of rabbits: a controlled randomized study
- Reliability of histopathologic diagnosis of fibrotic interstitial lung disease: an international collaborative standardization project
- DJ-1 binds to Rubicon to impair LC-3 associated phagocytosis
- Diagnostic accuracy of a clinical diagnosis of idiopathic pulmonary fibrosis: an international case–cohort study
Informações sobre o DOI: 10.1038/s41379-021-00772-3 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
003233331.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
