AIMC Topic: Crowdsourcing

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Does Surgeon Experience Correlate with Crowd-Sourced Skill Assessment in Robotic Bariatric Surgery?

The American surgeon Dec 1, 2022
BACKGROUND: The Global Evaluative Assessment of Robotic Skills (GEARS) rubric provides a measure of skill in robotic surgery. We hypothesize surgery performed by more experienced operators will be associated with higher GEARS scores.
Humans Robotic Surgical Procedures Bariatric Surgery Surgeons Crowdsourcing Clinical Competence Robotics
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Designing all-pay auctions using deep learning and multi-agent simulation.

Scientific reports Oct 8, 2022
We propose a multi-agent learning approach for designing crowdsourcing contests and All-Pay auctions. Prizes in contests incentivise contestants to expend effort on their entries, with different prize allocations resulting in different incentives and...
Motivation Crowdsourcing Computer Simulation Deep Learning
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Can images crowdsourced from the internet be used to train generalizable joint dislocation deep learning algorithms?

Skeletal radiology May 28, 2022
OBJECTIVE: Deep learning has the potential to automatically triage orthopedic emergencies, such as joint dislocations. However, due to the rarity of these injuries, collecting large numbers of images to train algorithms may be infeasible for many cen...
Algorithms Deep Learning Internet Joint Dislocations Crowdsourcing Humans
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An Exploratory Approach to Deriving Nutrition Information of Restaurant Food from Crowdsourced Food Images: Case of Hartford.

Nutrients Nov 18, 2021
Deep learning models can recognize the food item in an image and derive their nutrition information, including calories, macronutrients (carbohydrates, fats, and proteins), and micronutrients (vitamins and minerals). This technology has yet to be imp...
Humans Nutritive Value Connecticut Photography Deep Learning Food Analysis Nutrients Restaurants Census Tract Food Labeling Crowdsourcing
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Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO).

PLoS computational biology Oct 28, 2021
Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying ...
Molecular Sequence Annotation Computational Biology Gene Ontology Humans Crowdsourcing Databases, Genetic Proteins
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A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization.

JAMA network open Oct 1, 2021
IMPORTANCE: Machine learning could be used to predict the likelihood of diagnosis and severity of illness. Lack of COVID-19 patient data has hindered the data science community in developing models to aid in the response to the pandemic.
Washington Clinical Decision Rules COVID-19 Testing Crowdsourcing Child ROC Curve Humans Models, Statistical Machine Learning Area Under Curve Benchmarking Severity of Illness Index Hospitalization Adolescent Aged Child, Preschool Aged, 80 and over Middle Aged Prognosis COVID-19 Young Adult Infant Female Algorithms Infant, Newborn Adult Male
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Relation extraction from DailyMed structured product labels by optimally combining crowd, experts and machines.

Journal of biomedical informatics Sep 1, 2021
The effectiveness of machine learning models to provide accurate and consistent results in drug discovery and clinical decision support is strongly dependent on the quality of the data used. However, substantive amounts of open data that drive drug d...
Crowdsourcing Machine Learning Drug Repositioning
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A Time-Series-Based New Behavior Trace Model for Crowd Workers That Ensures Quality Annotation.

Sensors (Basel, Switzerland) Jul 23, 2021
Crowdsourcing is a new mode of value creation in which organizations leverage numerous Internet users to accomplish tasks. However, because these workers have different backgrounds and intentions, crowdsourcing suffers from quality concerns. In the l...
Crowdsourcing Humans Neural Networks, Computer Machine Learning
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Learning from crowds in digital pathology using scalable variational Gaussian processes.

Scientific reports Jun 2, 2021
The volume of labeled data is often the primary determinant of success in developing machine learning algorithms. This has increased interest in methods for leveraging crowds to scale data labeling efforts, and methods to learn from noisy crowd-sourc...
Histocytochemistry Humans Breast Neoplasms Normal Distribution Software Crowdsourcing Deep Learning Female
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Crowdsourcing airway annotations in chest computed tomography images.

PloS one Apr 22, 2021
Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotate...
Radiography, Thoracic Algorithms Humans Crowdsourcing Tomography, X-Ray Computed Machine Learning Lung
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