AIMC Topic: Crowdsourcing

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Hybrid Semantic Analysis for Mapping Adverse Drug Reaction Mentions in Tweets to Medical Terminology.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social networks, such as Twitter, have become important sources for active monitoring of user-reported adverse drug reactions (ADRs). Automatic extraction of ADR information can be crucial for healthcare providers, drug manufacturers, and consumers. ...

Crowdsourced validation of a machine-learning classification system for autism and ADHD.

Translational psychiatry
Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) together affect >10% of the children in the United States, but considerable behavioral overlaps between the two disorders can often complicate differential diagnosis. ...

Refining Automatically Extracted Knowledge Bases Using Crowdsourcing.

Computational intelligence and neuroscience
Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far from...

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...