AIMC Topic: Crowdsourcing

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Data quality in crowdsourcing and spamming behavior detection.

Behavior research methods Aug 8, 2025
As crowdsourcing emerges as an efficient and cost-effective method for obtaining labels for machine learning datasets, it is important to assess the quality of crowd-provided data to improve analysis performance and reduce biases in subsequent machin...
Markov Chains Data Accuracy Crowdsourcing Humans Machine Learning
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Aggregating soft labels from crowd annotations improves uncertainty estimation under distribution shift.

PloS one Jun 9, 2025
Selecting an effective training signal for machine learning tasks is difficult: expert annotations are expensive, and crowd-sourced annotations may not be reliable. Recent work has demonstrated that learning from a distribution over labels acquired f...
Machine Learning Humans Algorithms Crowdsourcing Uncertainty
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AI-imputed and crowdsourced price data show strong agreement with traditional price surveys in data-scarce environments.

PloS one Apr 8, 2025
Continuous access to up-to-date food price data is crucial for monitoring food security and responding swiftly to emerging risks. However, in many food-insecure countries, price data is often delayed, lacks spatial detail, or is unavailable during cr...
COVID-19 Surveys and Questionnaires Humans Artificial Intelligence Oryza Commerce Food Supply Crowdsourcing Nigeria Zea mays Food Security
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Impact of Image Content on Medical Crowdfunding Success: A Machine Learning Approach.

Journal of medical Internet research Nov 15, 2024
BACKGROUND: As crowdfunding sites proliferate, visual content often serves as the initial bridge connecting a project to its potential backers, underscoring the importance of image selection in effectively engaging an audience.
Crowdsourcing Fund Raising Machine Learning Neoplasms Humans
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Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort Collaborative.

EBioMedicine Sep 24, 2024
BACKGROUND: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term...
United States Post-Acute COVID-19 Syndrome Crowdsourcing SARS-CoV-2 Cohort Studies Humans COVID-19 Machine Learning Algorithms
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Machine learning surveillance of foodborne infectious diseases using wastewater microbiome, crowdsourced, and environmental data.

Water research Aug 21, 2024
Clostridium perfringens (CP) is a common cause of foodborne infection, leading to significant human health risks and a high economic burden. Thus, effective CP disease surveillance is essential for preventive and therapeutic interventions; however, c...
Microbiota Clostridium perfringens Wastewater Humans Crowdsourcing Foodborne Diseases Machine Learning
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Boosting wisdom of the crowd for medical image annotation using training performance and task features.

Cognitive research: principles and implications May 20, 2024
A crucial bottleneck in medical artificial intelligence (AI) is high-quality labeled medical datasets. In this paper, we test a large variety of wisdom of the crowd algorithms to label medical images that were initially classified by individuals recr...
Algorithms Adult Bayes Theorem Crowdsourcing Humans Artificial Intelligence
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Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.

Scientific reports Jan 23, 2024
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-de...
Crowdsourcing Colonoscopy Polyps Deep Learning Humans Computers
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Crowdsourcing image segmentation for deep learning: integrated platform for citizen science, paid microtask, and gamification.

Biomedizinische Technik. Biomedical engineering Dec 26, 2023
OBJECTIVES: Segmentation is crucial in medical imaging. Deep learning based on convolutional neural networks showed promising results. However, the absence of large-scale datasets and a high degree of inter- and intra-observer variations pose a bottl...
Crowdsourcing Humans Citizen Science Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted
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Crowd-Sourced Deep Learning for Intracranial Hemorrhage Identification: Wisdom of Crowds or Laissez-Faire.

AJNR. American journal of neuroradiology Jun 8, 2023
BACKGROUND AND PURPOSE: Researchers and clinical radiology practices are increasingly faced with the task of selecting the most accurate artificial intelligence tools from an ever-expanding range. In this study, we sought to test the utility of ensem...
Intracranial Hemorrhages Retrospective Studies Humans Crowdsourcing Deep Learning Artificial Intelligence
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