Zobrazeno 1 - 10
of 22 113
pro vyhledávání: '"Figueredo"'
Autor:
da Cunha ALG, Vasconcelos R, Di Sessa D, Sampaio G, Ramalhoto P, Zampieri BF, Deus BS, Vasconcelos S, Bellote T, Carvalho J, Petrone G, Figueredo V, Limongi Moreira G
Publikováno v:
Clinical, Cosmetic and Investigational Dermatology, Vol Volume 16, Pp 697-704 (2023)
Ana Lucia Gonzaga da Cunha,1 Rossana Vasconcelos,2 David Di Sessa,3 Gabriel Sampaio,4 Pitila Ramalhoto,5 Bruno F Zampieri,6 Bárbara S Deus,7 Suyan Vasconcelos,8 Talitha Bellote,9 Juiano Carvalho,10 Giseli Petrone,5 Vinicius Figueredo,11 Gustavo Limo
Externí odkaz:
https://doaj.org/article/e416778d318c45069324b454f37ed233
Autor:
Figueredo Pamela, Barrios Iván, O’Higgins Marcelo, Amarilla Diego, Almirón-Santacruz José, Melgarejo Osvaldo, Ruiz-Díaz Noelia, Castaldelli-Maia João Mauricio, Ventriglio Antonio, Torales Julio
Publikováno v:
Scandinavian Journal of Child and Adolescent Psychiatry and Psychology, Vol 10, Iss 1, Pp 58-63 (2022)
Several authors have pointed out that the use of smartphones might have an impact on mental health in general. Most of the evidences are focused on the incorrect or overblown use of smartphones, videogame or Internet, particularly focusing on related
Externí odkaz:
https://doaj.org/article/9fe3f8713c2947b4b192e8e56ce64892
Autor:
Boza Naranjo, Yennis Daliana, Figueredo Figueredo, Ana Luisa, Guerra Sánchez, Daramis, Méndez Álvarez, Jesús Emanuel
Publikováno v:
Agroecosistemas, Vol 9, Iss 3, Pp 57-66 (2021)
El artículo que se presenta tiene como propósito fundamental la propuesta de un programa de extensión forestal dirigido al restablecimiento de la especie Byrsonima crassifolia en la Comunidad Peralejo, del municipio Bayamo, provincia Granma. El pr
Externí odkaz:
https://doaj.org/article/4f9a2fafe780424593214e0fdc337ea4
Autor:
Mitchell-White, James, Omdivar, Reza, Urwin, Esmond, Sivakumar, Karthikeyan, Li, Ruizhe, Rae, Andy, Wang, Xiaoyan, Mina, Theresia, Chambers, John, Figueredo, Grazziela, Quinlan, Philip R
This paper introduces Llettuce, an open-source tool designed to address the complexities of converting medical terms into OMOP standard concepts. Unlike existing solutions such as the Athena database search and Usagi, which struggle with semantic nua
Externí odkaz:
http://arxiv.org/abs/2410.09076
Autor:
Kadi, Halid Abdulrahim, Chandy, Jose Alex, Figueredo, Luis, Terzić, Kasim, Caleb-Solly, Praminda
The fidelity gap between simulation-trained vision-based data-driven cloth neural controllers and real-world operation impedes reliable deployment of methods from simulation into physical trials. Real-world grasping errors, such as misgrasping and mu
Externí odkaz:
http://arxiv.org/abs/2409.15159
We propose a method to systematically represent both the static and the dynamic components of environments, i.e. objects and agents, as well as the changes that are happening in the environment, i.e. the actions and skills performed by agents. Our ap
Externí odkaz:
http://arxiv.org/abs/2409.08853
Publikováno v:
Agroecosistemas, Vol 8, Iss 1, Pp 59-63 (2020)
El trabajo se realizó con el objetivo de caracterizar la vegetación de un sector del bosque protector de agua y suelo del río Yara, Municipio Bartolomé Masó, Provincia Granma. Se realizó un inventario florístico donde se levantaron 12 transect
Externí odkaz:
https://doaj.org/article/94f164e2397b4a55b69ef0c4e2ad6bb6
Data is crucial for evidence-based policymaking and enhancing public services, including those at the Ministry of Finance of the Republic of Indonesia. However, the complexity and dynamic nature of governmental financial data and regulations can hind
Externí odkaz:
http://arxiv.org/abs/2407.21459
Automatic radiology report generation can alleviate the workload for physicians and minimize regional disparities in medical resources, therefore becoming an important topic in the medical image analysis field. It is a challenging task, as the comput
Externí odkaz:
http://arxiv.org/abs/2405.12833
Deformable image registration (alignment) is highly sought after in numerous clinical applications, such as computer aided diagnosis and disease progression analysis. Deep Convolutional Neural Network (DCNN)-based image registration methods have demo
Externí odkaz:
http://arxiv.org/abs/2405.10068