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Refinado por: Biblioteca: FM - Fac. Medicina remover
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1
Recognition of Foot-Ankle Movement Patterns in Long-Distance Runners With Different Experience Levels Using Support Vector Machines
Recognition of Foot-Ankle Movement Patterns in Long-Distance Runners With Different Experience Levels Using Support Vector Machines
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Artigo 		Adicionar ao Meu Espaço

Recognition of Foot-Ankle Movement Patterns in Long-Distance Runners With Different Experience Levels Using Support Vector Machines

Eneida Yuri Suda Ricky Watari; Alessandra Bento Matias; Isabel de Camargo Neves Sacco

Frontiers in bioengineering and biotechnology v. 8, article ID 576, 11p, 2020

Lausanne 2020

Acesso online. A biblioteca também possui exemplares impressos.

2
Complete blood count and C-reactive protein to predict positive blood culture among neonates using machine learning algorithms
Complete blood count and C-reactive protein to predict positive blood culture among neonates using machine learning algorithms
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Complete blood count and C-reactive protein to predict positive blood culture among neonates using machine learning algorithms

Felipe Yu Matsushita Vera Lucia Jornada Krebs; Werther Brunow de Carvalho

Clinics v. 78, article ID 100148, 6p, 2023

São Paulo 2023

Acesso online. A biblioteca também possui exemplares impressos.

3
The learning curve of bilateral laparoscopic varicocelectomy a prospective study
The learning curve of bilateral laparoscopic varicocelectomy a prospective study
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The learning curve of bilateral laparoscopic varicocelectomy a prospective study

Mikhael Belkovsky Carlo Camargo Passerotti; Linda Ferreira Maximiano; José Pinhata Otoch; José Arnaldo Shiomi da Cruz

Revista do colégio brasileiro de cirurgiões v. 50, p. e20233456, 2023

São Paulo 2023

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4
Suicide risk classification with machine learning techniques in a large Brazilian community sample
Suicide risk classification with machine learning techniques in a large Brazilian community sample
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Suicide risk classification with machine learning techniques in a large Brazilian community sample

Thiago Henrique Roza Gabriel de Souza Seibel; Mariana Recamonde-Mendoza; Paulo Andrade Lotufo; Isabela Judith Martins Benseñor; Ives Cavalcante Passos; Andre Russowsky Brunoni

Psychiatry research v. 325, article ID 115258, 10p, 2023

Clare 2023

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5
Web based thoracic surgery online course Increased access, connecting people and decreasing inequalities. Feasibility results
Web based thoracic surgery online course Increased access, connecting people and decreasing inequalities. Feasibility results
Material Type:
Artigo de Congresso 		Adicionar ao Meu Espaço

Web based thoracic surgery online course Increased access, connecting people and decreasing inequalities. Feasibility results

Ricardo Mingarini Terra Pedro Henrique Xavier Nabuco de Araújo; Alessandro Wasun Mariani; Alberto Jorge Monteiro Dela Vega; Paulo Manuel Pego-Fernandes; IASLC Latin American Conference Lung Cancer (6 2014 Lima/Peru)

Journal of Thoracic Oncology Hagerstown v. 9, n. 9, suppl. 3, p. S181, res. P1.55, 2014

Hagerstown 2014

Localização: FM - Fac. Medicina    (BCSEP 544 2014 )(Acessar)

6
Using structural MRI to identify bipolar disorders-13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
Using structural MRI to identify bipolar disorders-13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
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Using structural MRI to identify bipolar disorders-13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Abraham Nunes Hugo G Schnack; Christopher R. K Ching; Ingrid Agartz; Theophilus N Akudjedu; Martin Alda; Dag Alnaes; Silvia Alonso-Lana; Jochen Bauer; Geraldo Busatto Filho

Molecular psychiatry v. 25, n. 9, p. 2130-2143, 2020

London 2020

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7
Biventricular imaging markers to predict outcomes in non-compaction cardiomyopathy a machine learning study
Biventricular imaging markers to predict outcomes in non-compaction cardiomyopathy a machine learning study
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Biventricular imaging markers to predict outcomes in non-compaction cardiomyopathy a machine learning study

Camila Rocon Mahdi Tabassian; Marcelo Dantas Tavares de Melo; Jose Arimateia de Araujo Filho; Cesar Jose Grupi; Jose Rodrigues Parga Filho; Edimar Alcides Bocchi; Jan D'hooge; Vera Maria Cury Salemi

Esc heart failure v. 7, n. 5, p. 2431-2439, 2020

San Francisco 2020

Acesso online. A biblioteca também possui exemplares impressos.

8
Using supervised machine learning on neuropsychological data to distinguish OCD patients with and without sensory phenomena from healthy controls
Using supervised machine learning on neuropsychological data to distinguish OCD patients with and without sensory phenomena from healthy controls
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Artigo 		Adicionar ao Meu Espaço

Using supervised machine learning on neuropsychological data to distinguish OCD patients with and without sensory phenomena from healthy controls

C. A Stamatis M. C Batistuzzo; T Tanamatis; Eurípedes Constantino Miguel Filho; M. Q Hoexter; K. R Timpano

British journal of clinical psychology v. 61, n. 01, p. 77-98, 2021

Hoboken 2021

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9
Identifying clinical phenotypes in extremely low birth weight infants-an unsupervised machine learning approach
Identifying clinical phenotypes in extremely low birth weight infants-an unsupervised machine learning approach
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Identifying clinical phenotypes in extremely low birth weight infants-an unsupervised machine learning approach

Felipe Yu Matsushita Vera Lucia Jornada Krebs; Werther Brunow de Carvalho

European journal of pediatrics v. 181, n. 3, p. 1085-1097, 2022

New York 2022

Acesso online. A biblioteca também possui exemplares impressos.

10
Two-year death prediction models among patients with Chagas Disease using machine learning-based methods
Two-year death prediction models among patients with Chagas Disease using machine learning-based methods
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Two-year death prediction models among patients with Chagas Disease using machine learning-based methods

Ariela Mota Ferreira Laercio Ives Santos; Ester Cerdeira Sabino; Antonio Luiz Pinho Y Ribeiro; Lea Campos de Oliveira-da Silva; Renata Fiuza Y Damasceno; Marcos Flavio Silveira Vasconcelos D'angelo; Maria do Carmo Pereira Y Nunes; Desiree Sant'Ana Haikal

Plos neglected tropical diseases v. 16, n. 4, article ID e0010356, 16p, 2022

San Francisco 2022

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Deste Autor:

  1. Kowalski, L
  2. Vargas, P
  3. Lopes, M
  4. Araujo, A
  5. Krebs, V

Neste Assunto:

  1. Aprendizado Computacional
  2. Inteligência Artificial
  3. Machine Learning
  4. Aprendizado De Máquina
  5. Artificial Intelligence

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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