AIMC Topic: Crowdsourcing

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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.

A fusocelular skin dataset with whole slide images for deep learning models.

Scientific data
Cutaneous spindle cell (CSC) lesions encompass a spectrum from benign to malignant neoplasms, often posing significant diagnostic challenges. Computer-aided diagnosis systems offer a promising solution to make pathologists' decisions objective and fa...

Combining collective and artificial intelligence for global health diseases diagnosis using crowdsourced annotated medical images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Visual inspection of microscopic samples is still the gold standard diagnostic methodology for many global health diseases. Soil-transmitted helminth infection affects 1.5 billion people worldwide, and is the most prevalent disease among the Neglecte...

A new approach and gold standard toward author disambiguation in MEDLINE.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Author-centric analyses of fast-growing biomedical reference databases are challenging due to author ambiguity. This problem has been mainly addressed through author disambiguation using supervised machine-learning algorithms. Such algorit...

Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting.

JAMA oncology
IMPORTANCE: Radiation therapy (RT) is a critical cancer treatment, but the existing radiation oncologist work force does not meet growing global demand. One key physician task in RT planning involves tumor segmentation for targeting, which requires s...

Learning From Peers' Eye Movements in the Absence of Expert Guidance: A Proof of Concept Using Laboratory Stock Trading, Eye Tracking, and Machine Learning.

Cognitive science
Existing research shows that people can improve their decision skills by learning what experts paid attention to when faced with the same problem. However, in domains like financial education, effective instruction requires frequent, personalized fee...

Fine-Tuning Deep Learning by Crowd Participation.

IEEE pulse
One of the major challenges currently facing researchers in applying deep learning (DL) models to medical image analysis is the limited amount of annotated data. Collecting such ground-truth annotations requires domain knowledge, cost, and time, maki...

Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make th...

The effects of auditory and visual cues on timing synchronicity for robotic rehabilitation.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
In this paper, we explore how the integration of auditory and visual cues can help teach the timing of motor skills for the purpose of motor function rehabilitation. We conducted a study using Amazon's Mechanical Turk in which 106 participants played...