Multiethnic polygenic risk scores improve risk prediction in diverse populations
Sign Up to like & getrecommendations! Published in 2017 at "Genetic Epidemiology"
DOI: 10.1002/gepi.22083
Abstract: Methods for genetic risk prediction have been widely investigated in recent years. However, most available training data involves European samples, and it is currently unclear how to accurately predict disease risk in other populations. Previous… read more here.
Keywords: polygenic risk; risk prediction; risk; training data ... See more keywords
Privacy preserving distributed training of neural networks
Sign Up to like & getrecommendations! Published in 2020 at "Neural Computing and Applications"
DOI: 10.1007/s00521-020-04880-0
Abstract: L earnae is a system aiming to achieve a fully distributed way of neural network training. It follows a “Vires in Numeris” approach, combining the resources of commodity personal computers. It has a full peer-to-peer… read more here.
Keywords: network; privacy preserving; training data; distributed training ... See more keywords
Detection and Labeling of Vertebrae in MR Images Using Deep Learning with Clinical Annotations as Training Data
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Digital Imaging"
DOI: 10.1007/s10278-017-9945-x
Abstract: The purpose of this study was to investigate the potential of using clinically provided spine label annotations stored in a single institution image archive as training data for deep learning-based vertebral detection and labeling pipelines.… read more here.
Keywords: detection; image; training data; using deep ... See more keywords
Effect of Training Data Volume on Performance of Convolutional Neural Network Pneumothorax Classifiers
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Digital Imaging"
DOI: 10.1007/s10278-022-00594-y
Abstract: Large datasets with high-quality labels required to train deep neural networks are challenging to obtain in the radiology domain. This work investigates the effect of training dataset size on the performance of deep learning classifiers,… read more here.
Keywords: effect training; radiology; training data; performance ... See more keywords
Selective harvesting over networks
Sign Up to like & getrecommendations! Published in 2017 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-017-0523-0
Abstract: Active search on graphs focuses on collecting certain labeled nodes (targets) given global knowledge of the network topology and its edge weights (encoding pairwise similarities) under a query budget constraint. However, in most current networks,… read more here.
Keywords: network; training data; topology; selective harvesting ... See more keywords
The impact of imbalanced training data on machine learning for author name disambiguation
Sign Up to like & getrecommendations! Published in 2018 at "Scientometrics"
DOI: 10.1007/s11192-018-2865-9
Abstract: In supervised machine learning for author name disambiguation, negative training data are often dominantly larger than positive training data. This paper examines how the ratios of negative to positive training data can affect the performance… read more here.
Keywords: name disambiguation; machine learning; training data; training ... See more keywords
User-adaptive models for activity and emotion recognition using deep transfer learning and data augmentation
Sign Up to like & getrecommendations! Published in 2019 at "User Modeling and User-Adapted Interaction"
DOI: 10.1007/s11257-019-09248-1
Abstract: Building predictive models for human-interactive systems is a challenging task. Every individual has unique characteristics and behaviors. A generic human–machine system will not perform equally well for each user given the between-user differences. Alternatively, a… read more here.
Keywords: adaptive models; using deep; training data; deep transfer ... See more keywords
Which is the Better Inpainted Image?Training Data Generation Without Any Manual Operations
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Computer Vision"
DOI: 10.1007/s11263-018-1132-0
Abstract: This paper proposes a learning-based quality evaluation framework for inpainted results that does not require any subjectively annotated training data. Image inpainting, which removes and restores unwanted regions in images, is widely acknowledged as a… read more here.
Keywords: data generation; image; training data; better inpainted ... See more keywords
Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Signal Processing Systems"
DOI: 10.1007/s11265-021-01715-6
Abstract: Anomaly detection is of great interest in fields where abnormalities need to be identified and corrected (e.g., medicine and finance). Deep learning methods for this task often rely on autoencoder reconstruction error, sometimes in conjunction… read more here.
Keywords: lipschitz; training data; anomaly detection; detection ... See more keywords
Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-019-01919-z
Abstract: PurposeCancers are almost always diagnosed by morphologic features in tissue sections. In this context, machine learning tools provide new opportunities to describe tumor immune cell interactions within the tumor microenvironment and thus provide phenotypic information… read more here.
Keywords: classification; training data; tissue; cell ... See more keywords
Generation of synthetic training data for SEEG electrodes segmentation
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-022-02585-4
Abstract: Stereoelectroencephalography (SEEG) is a minimally invasive surgical procedure, used to locate epileptogenic zones. An accurate identification of the metallic contacts recording the SEEG signal is crucial to ensure effectiveness of the upcoming treatment. However, due… read more here.
Keywords: synthetic data; training data; segmentation; seeg ... See more keywords