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Refinado por: assunto: Pneumonia remover
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Effects on postgraduate-year-I residents of simulation-based learning compared to traditional lecture-style education led by postgraduate-year-II residents: a pilot study
Effects on postgraduate-year-I residents of simulation-based learning compared to traditional lecture-style education led by postgraduate-year-II residents: a pilot study
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Effects on postgraduate-year-I residents of simulation-based learning compared to traditional lecture-style education led by postgraduate-year-II residents: a pilot study

Yamamoto, Akira ; Obika, Mikako ; Mandai, Yasuhiro ; Murakami, Taku ; Miyoshi, Tomoko ; Ino, Hideo ; Kataoka, Hitomi ; Otsuka, Fumio

BMC medical education, 2019-03, Vol.19 (1), p.87-87, Article 87 [Periódico revisado por pares]

England: BioMed Central Ltd

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2
The Multi-Task Deep Model-Based Pneumonia Detection
The Multi-Task Deep Model-Based Pneumonia Detection
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The Multi-Task Deep Model-Based Pneumonia Detection

Ai, Xingfang ; Li, Zhongliang ; Cao, Min ; Li, Xuechen

Journal of physics. Conference series, 2021-04, Vol.1883 (1), p.12034 [Periódico revisado por pares]

Bristol: IOP Publishing

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3
A framework for feature extraction from hospital medical data with applications in risk prediction
A framework for feature extraction from hospital medical data with applications in risk prediction
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A framework for feature extraction from hospital medical data with applications in risk prediction

Tran, Truyen ; Luo, Wei ; Phung, Dinh ; Gupta, Sunil ; Rana, Santu ; Kennedy, Richard Lee ; Larkins, Ann ; Venkatesh, Svetha

BMC bioinformatics, 2014-12, Vol.15 (1), p.425-425, Article 425 [Periódico revisado por pares]

England: BioMed Central Ltd

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4
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
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Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

Rajpurkar, Pranav ; Irvin, Jeremy ; Ball, Robyn L ; Zhu, Kaylie ; Yang, Brandon ; Mehta, Hershel ; Duan, Tony ; Ding, Daisy ; Bagul, Aarti ; Langlotz, Curtis P ; Patel, Bhavik N ; Yeom, Kristen W ; Shpanskaya, Katie ; Blankenberg, Francis G ; Seekins, Jayne ; Amrhein, Timothy J ; Mong, David A ; Halabi, Safwan S ; Zucker, Evan J ; Ng, Andrew Y ; Lungren, Matthew P Sheikh, Aziz

PLoS medicine, 2018-11, Vol.15 (11), p.e1002686-e1002686 [Periódico revisado por pares]

United States: Public Library of Science

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5
RANDGAN: Randomized generative adversarial network for detection of COVID-19 in chest X-ray
RANDGAN: Randomized generative adversarial network for detection of COVID-19 in chest X-ray
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RANDGAN: Randomized generative adversarial network for detection of COVID-19 in chest X-ray

Motamed, Saman ; Rogalla, Patrik ; Khalvati, Farzad

Scientific reports, 2021-04, Vol.11 (1), p.8602-8602, Article 8602 [Periódico revisado por pares]

England: Nature Publishing Group

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6
Emb-trattunet: a novel edge loss function and transformer-CNN architecture for multi-classes pneumonia infection segmentation in low annotation regimes
Emb-trattunet: a novel edge loss function and transformer-CNN architecture for multi-classes pneumonia infection segmentation in low annotation regimes
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Emb-trattunet: a novel edge loss function and transformer-CNN architecture for multi-classes pneumonia infection segmentation in low annotation regimes

Bougourzi, Fares ; Dornaika, Fadi ; Nakib, Amir ; Taleb-Ahmed, Abdelmalik

The Artificial intelligence review, 2024-03, Vol.57 (4), p.90, Article 90 [Periódico revisado por pares]

Dordrecht: Springer Netherlands

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7
MultiCheXNet: A Multi-Task Learning Deep Network For Pneumonia-like Diseases Diagnosis From X-ray Scans
MultiCheXNet: A Multi-Task Learning Deep Network For Pneumonia-like Diseases Diagnosis From X-ray Scans
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MultiCheXNet: A Multi-Task Learning Deep Network For Pneumonia-like Diseases Diagnosis From X-ray Scans

Abdullah, Tarek Farag ; Raafat Abd El-Wahab, Ahmed ; Mahmoud Nada ; Abd El-Hakeem, Mohamed Yasser ; Omar Sayed Mahmoud ; Rashwan, Reem Khaled ; Ahmad El Sallab

arXiv.org, 2020-08

Ithaca: Cornell University Library, arXiv.org

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8
Efficient ensemble for image-based identification of Pneumonia utilizing deep CNN and SGD with warm restarts
Efficient ensemble for image-based identification of Pneumonia utilizing deep CNN and SGD with warm restarts
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Efficient ensemble for image-based identification of Pneumonia utilizing deep CNN and SGD with warm restarts

Vrbančič, Grega ; Podgorelec, Vili

Expert systems with applications, 2022-01, Vol.187, p.115834, Article 115834 [Periódico revisado por pares]

New York: Elsevier Ltd

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9
In-silico study of antisense oligonucleotide antibiotics
In-silico study of antisense oligonucleotide antibiotics
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In-silico study of antisense oligonucleotide antibiotics

Chen, Erica S. ; Ho, Eric S.

PeerJ (San Francisco, CA), 2023-11, Vol.11, p.e16343-e16343, Article e16343 [Periódico revisado por pares]

San Diego: PeerJ, Inc

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10
Assessing the time use and payments of multipurpose community health workers for the various roles they play—a quantitative study of the Mitanin programme in India
Assessing the time use and payments of multipurpose community health workers for the various roles they play—a quantitative study of the Mitanin programme in India
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Assessing the time use and payments of multipurpose community health workers for the various roles they play—a quantitative study of the Mitanin programme in India

Garg, Samir ; Dewangan, Mukesh ; Nanda, Prabodh ; C, Krishnendhu ; Sahu, Ashu ; Xalxo, Lalita

BMC health services research, 2022-08, Vol.22 (1), p.1-1018, Article 1018 [Periódico revisado por pares]

London: BioMed Central

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Deste Autor:

  1. Borges, S
  2. Universidade Estadual De Campinas
  3. Santos, E
  4. Marins, P
  5. Takahashi De Oliveira, S

Neste Assunto:

  1. Pneumonia
  2. Pneumonia
  3. Science & Technology
  4. Life Sciences & Biomedicine
  5. Humans

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

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