AIMC Topic: Data Curation

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A Generic Human-Machine Annotation Framework Based on Dynamic Cooperative Learning.

IEEE transactions on cybernetics
The task of obtaining meaningful annotations is a tedious work, incurring considerable costs and time consumption. Dynamic active learning and cooperative learning are recently proposed approaches to reduce human effort of annotating data with subjec...

Incorporating dictionaries into deep neural networks for the Chinese clinical named entity recognition.

Journal of biomedical informatics
Clinical named entity recognition aims to identify and classify clinical terms such as diseases, symptoms, treatments, exams, and body parts in electronic health records, which is a fundamental and crucial task for clinical and translational research...

MCN: A comprehensive corpus for medical concept normalization.

Journal of biomedical informatics
Normalization of clinical text involves linking different ways of talking about the same clinical concept to the same term in the standardized vocabulary. To date, very few annotated corpora for normalization have been available, and existing corpora...

Generative Adversarial Networks for Facilitating Stain-Independent Supervised and Unsupervised Segmentation: A Study on Kidney Histology.

IEEE transactions on medical imaging
A major challenge in the field of segmentation in digital pathology is given by the high effort for manual data annotations in combination with many sources introducing variability in the image domain. This requires methods that are able to cope with...

MAIA-A machine learning assisted image annotation method for environmental monitoring and exploration.

PloS one
Digital imaging has become one of the most important techniques in environmental monitoring and exploration. In the case of the marine environment, mobile platforms such as autonomous underwater vehicles (AUVs) are now equipped with high-resolution c...

Ossification area localization in pediatric hand radiographs using deep neural networks for object detection.

PloS one
BACKGROUND: Detection of ossification areas of hand bones in X-ray images is an important task, e.g. as a preprocessing step in automated bone age estimation. Deep neural networks have emerged recently as de facto standard detection methods, but thei...

OC-2-KB: integrating crowdsourcing into an obesity and cancer knowledge base curation system.

BMC medical informatics and decision making
BACKGROUND: There is strong scientific evidence linking obesity and overweight to the risk of various cancers and to cancer survivorship. Nevertheless, the existing online information about the relationship between obesity and cancer is poorly organi...

Consistent Semantic Annotation of Outdoor Datasets via 2D/3D Label Transfer.

Sensors (Basel, Switzerland)
The advance of scene understanding methods based on machine learning relies on the availability of large ground truth datasets, which are essential for their training and evaluation. Construction of such datasets with imagery from real sensor data ho...

Using machine learning tools for protein database biocuration assistance.

Scientific reports
Biocuration in the omics sciences has become paramount, as research in these fields rapidly evolves towards increasingly data-dependent models. As a result, the management of web-accessible publicly-available databases becomes a central task in biolo...

Image set for deep learning: field images of maize annotated with disease symptoms.

BMC research notes
OBJECTIVES: Automated detection and quantification of plant diseases would enable more rapid gains in plant breeding and faster scouting of farmers' fields. However, it is difficult for a simple algorithm to distinguish between the target disease and...