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BMC Bioinformatics
|
September 25, 2019
Machine learning for discovering missing or wrong protein function annotations : A comparison using updated benchmark datasets
Felipe Kenji Nakano, Mathias Lietaert, Celine Vens
Computers in Biology and Medicine
|
December 18, 2022
Leveraging class hierarchy for detecting missing annotations on hierarchical multi-label classification
Miguel Romero, Felipe Kenji Nakano, Jorge Finke, et al.
IEEE Transactions on Neural Networks and Learning Systems
|
October 21, 2022
Online Extra Trees Regressor
Saulo Martiello Mastelini, Felipe Kenji Nakano, Celine Vens, et al.
Intensive Care Medicine Experimental
|
October 20, 2025
Correction: Development and validation of a machine learning model for early prediction of intensive care unit acquired weakness
Felipe Kenji Nakano, Nathalie Van Aerde, Gregoire Coppens, et al.
Intensive Care Medicine Experimental
|
September 30, 2025
Development and validation of a machine learning model for early prediction of intensive care unit acquired weakness
Felipe Kenji Nakano, Nathalie Van Aerde, Grégoire Coppens, et al.
Computer Methods and Programs in Biomedicine
|
April 13, 2024
Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admission
Felipe Kenji Nakano, Karolijn Dulfer, Ilse Vanhorebeek, et al.
BMC Nephrology
|
January 30, 2025
Enhancing individual glomerular filtration rate assessment: can we trust the equation? Development and validation of machine learning models to assess the trustworthiness of estimated GFR compared to measured GFR
Antoine Lanot, Anna Akesson, Felipe Kenji Nakano, et al.
Scientific Reports
|
November 2, 2024
Comparison between the EKFC-equation and machine learning models to predict Glomerular Filtration Rate
Felipe Kenji Nakano, Anna Åkesson, Jasper de Boer, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 8) with videos related to
Sort By:
Page
of 1
BMC Bioinformatics
|
September 25, 2019
Machine learning for discovering missing or wrong protein function annotations : A comparison using updated benchmark datasets
Felipe Kenji Nakano, Mathias Lietaert, Celine Vens
Computers in Biology and Medicine
|
December 18, 2022
Leveraging class hierarchy for detecting missing annotations on hierarchical multi-label classification
Miguel Romero, Felipe Kenji Nakano, Jorge Finke, et al.
IEEE Transactions on Neural Networks and Learning Systems
|
October 21, 2022
Online Extra Trees Regressor
Saulo Martiello Mastelini, Felipe Kenji Nakano, Celine Vens, et al.
Intensive Care Medicine Experimental
|
October 20, 2025
Correction: Development and validation of a machine learning model for early prediction of intensive care unit acquired weakness
Felipe Kenji Nakano, Nathalie Van Aerde, Gregoire Coppens, et al.
Intensive Care Medicine Experimental
|
September 30, 2025
Development and validation of a machine learning model for early prediction of intensive care unit acquired weakness
Felipe Kenji Nakano, Nathalie Van Aerde, Grégoire Coppens, et al.
Computer Methods and Programs in Biomedicine
|
April 13, 2024
Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admission
Felipe Kenji Nakano, Karolijn Dulfer, Ilse Vanhorebeek, et al.
BMC Nephrology
|
January 30, 2025
Enhancing individual glomerular filtration rate assessment: can we trust the equation? Development and validation of machine learning models to assess the trustworthiness of estimated GFR compared to measured GFR
Antoine Lanot, Anna Akesson, Felipe Kenji Nakano, et al.
Scientific Reports
|
November 2, 2024
Comparison between the EKFC-equation and machine learning models to predict Glomerular Filtration Rate
Felipe Kenji Nakano, Anna Åkesson, Jasper de Boer, et al.
Page
of 1