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mtPCDI - a machine learning-based prognostic model for prostate cancer recurrence
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mtPCDI - a machine learning-based prognostic model for prostate cancer recurrence

Added by Liam
16
A review of model evaluation metrics for machine learning in genetics and genomics
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A review of model evaluation metrics for machine learning in genetics and genomics

Added by Oliver
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Identification of Significant Biomarkers for Predicting the Risk of Bipolar Disorder with Arteriosclerosis - based on integrative bioinformatics and machine learning
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Identification of Significant Biomarkers for Predicting the Risk of Bipolar Disorder with Arteriosclerosis - based on integrative bioinformatics and machine learning

Added by Liam
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Regularization of Riemannian optimization - Application to process tomography and quantum machine learning
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Regularization of Riemannian optimization - Application to process tomography and quantum machine learning

Added by Liam
15
Classical integrability in the presence of a cosmological constant - analytic and machine learning results
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Classical integrability in the presence of a cosmological constant - analytic and machine learning results

Added by Liam
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Symbolic Integration Algorithm Selection with Machine Learning - LSTMs vs Tree LSTMs - research paper
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Symbolic Integration Algorithm Selection with Machine Learning - LSTMs vs Tree LSTMs - research paper

Added by Liam
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Machine learning in physical activity, sedentary, and sleep behavior research
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Machine learning in physical activity, sedentary, and sleep behavior research

Added by Liam
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Beam Training in mmWave Vehicular Systems - Machine Learning for Decoupling Beam Selection
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Beam Training in mmWave Vehicular Systems - Machine Learning for Decoupling Beam Selection

Added by Liam
19
Structural properties of amorphous Na3 OCl electrolyte by first-principles and machine learning molecular dynamics
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Structural properties of amorphous Na3 OCl electrolyte by first-principles and machine learning molecular dynamics

Added by Liam
14
Strategies for Machine Learning Applied to Noisy HEP Datasets - Modular Solid State Detectors from SuperCDMS
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Strategies for Machine Learning Applied to Noisy HEP Datasets - Modular Solid State Detectors from SuperCDMS

Added by Liam
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Twenty Constructionist Things to Do with Artificial Intelligence and Machine Learning - Paper overview
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Twenty Constructionist Things to Do with Artificial Intelligence and Machine Learning - Paper overview

Added by Liam
17
ALICE - Combining Feature Selection and Inter-Rater Agreeability for Machine Learning Insights
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ALICE - Combining Feature Selection and Inter-Rater Agreeability for Machine Learning Insights

Added by Liam
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Tell Machine Learning Potentials What They are Needed for - Simulation-Oriented Training Exemplified for Glycine
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Tell Machine Learning Potentials What They are Needed for - Simulation-Oriented Training Exemplified for Glycine

Added by Liam
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Biases and Ethical considerations for Machine Learning pipelines in the Computational Social Sciences - Abstract
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Biases and Ethical considerations for Machine Learning pipelines in the Computational Social Sciences - Abstract

Added by Liam
21
Machine learning based endothelial cell image analysis of patients undergoing descemet membrane endothelial keratoplasty surgery
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Machine learning based endothelial cell image analysis of patients undergoing descemet membrane endothelial keratoplasty surgery

Added by Liam
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