Privacy-preserving heterogeneous network embedding for clinical events (2021)
- Authors:
- USP affiliated authors: MARCACINI, RICARDO MARCONDES - ICMC ; PIMENTEL, MARIA DA GRAÇA CAMPOS - ICMC ; OLIVEIRA, GUSTAVO LIMA DE - ICMC
- Unidade: ICMC
- Subjects: REDES DE INFORMAÇÃO; APRENDIZADO COMPUTACIONAL; SISTEMAS DE INFORMAÇÃO HOSPITALAR
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: Systems and Machine Learning Foundation
- Publisher place: Indio
- Date published: 2021
- Source:
- Título do periódico: Proceedings
- Conference titles: Conference on Machine Learning and Systems - MLSys
-
ABNT
OLIVEIRA, Gustavo Lima de e MARCACINI, Ricardo Marcondes e PIMENTEL, Maria da Graça Campos. Privacy-preserving heterogeneous network embedding for clinical events. 2021, Anais.. Indio: Systems and Machine Learning Foundation, 2021. Disponível em: https://gnnsys.github.io/papers/GNNSys21_paper_19.pdf. Acesso em: 28 mar. 2024. -
APA
Oliveira, G. L. de, Marcacini, R. M., & Pimentel, M. da G. C. (2021). Privacy-preserving heterogeneous network embedding for clinical events. In Proceedings. Indio: Systems and Machine Learning Foundation. Recuperado de https://gnnsys.github.io/papers/GNNSys21_paper_19.pdf -
NLM
Oliveira GL de, Marcacini RM, Pimentel M da GC. Privacy-preserving heterogeneous network embedding for clinical events [Internet]. Proceedings. 2021 ;[citado 2024 mar. 28 ] Available from: https://gnnsys.github.io/papers/GNNSys21_paper_19.pdf -
Vancouver
Oliveira GL de, Marcacini RM, Pimentel M da GC. Privacy-preserving heterogeneous network embedding for clinical events [Internet]. Proceedings. 2021 ;[citado 2024 mar. 28 ] Available from: https://gnnsys.github.io/papers/GNNSys21_paper_19.pdf - Named Entity Recognition approaches applied to legal document segmentation
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