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Crowdsourcing

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A Frequency-based Strategy of Obtaining Sentences from Clinical Data Repository for Crowdsourcing.

Studies in health technology and informatics
In clinical NLP, one major barrier to adopting crowdsourcing for NLP annotation is the issue of confidentiality for protected health information (PHI) in clinical narratives. In this paper, we investigated the use of a frequency-based approach to ext...

Validation of a Crowdsourcing Methodology for Developing a Knowledge Base of Related Problem-Medication Pairs.

Applied clinical informatics
BACKGROUND: Clinical knowledge bases of problem-medication pairs are necessary for many informatics solutions that improve patient safety, such as clinical summarization. However, developing these knowledge bases can be challenging.

Crowdsourcing and curation: perspectives from biology and natural language processing.

Database : the journal of biological databases and curation
Crowdsourcing is increasingly utilized for performing tasks in both natural language processing and biocuration. Although there have been many applications of crowdsourcing in these fields, there have been fewer high-level discussions of the methodol...

Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

Database : the journal of biological databases and curation
Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources...

Learning to Select Supplier Portfolios for Service Supply Chain.

PloS one
The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier p...

Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response.

Big data
Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial...

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images.

IEEE transactions on medical imaging
The lack of publicly available ground-truth data has been identified as the major challenge for transferring recent developments in deep learning to the biomedical imaging domain. Though crowdsourcing has enabled annotation of large scale databases f...

Is the crowd better as an assistant or a replacement in ontology engineering? An exploration through the lens of the Gene Ontology.

Journal of biomedical informatics
Biomedical ontologies contain errors. Crowdsourcing, defined as taking a job traditionally performed by a designated agent and outsourcing it to an undefined large group of people, provides scalable access to humans. Therefore, the crowd has the pote...