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gptkbp:instance_of
|
gptkb:challenges
|
|
gptkbp:aims_to_improve
|
diagnostic accuracy in pathology
|
|
gptkbp:challenges
|
data variability
|
|
gptkbp:collaborated_with
|
technology companies
|
|
gptkbp:encourages
|
collaboration among institutions
|
|
gptkbp:events
|
gptkb:Camelyon17
|
|
gptkbp:feedback_mechanism
|
participant surveys
|
|
gptkbp:first_held
|
gptkb:2016
|
|
gptkbp:has_awards
|
best performance awards
|
|
gptkbp:has_data_privacy_considerations
|
patient data protection
|
|
gptkbp:has_evaluation_metric
|
area under the curve (AUC)
|
|
gptkbp:has_impact_on
|
clinical decision making
training of pathologists
|
|
gptkbp:has_multiple_phases
|
training phase and testing phase
|
|
gptkbp:has_participants
|
researchers and developers
|
|
gptkbp:has_publications
|
related research papers
|
|
gptkbp:has_results_published_in
|
gptkb:academic_journals
|
|
gptkbp:has_website
|
gptkb:camelyonchallenge.org
|
|
gptkbp:hosted_by
|
gptkb:Kaggle
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Camelyon challenge
|
|
gptkbp:includes
|
training and test data
|
|
gptkbp:is_analyzed_in
|
data scientists
|
|
gptkbp:is_associated_with
|
gptkb:AI_technology
|
|
gptkbp:is_collaborative_with
|
multi-institutional effort
|
|
gptkbp:is_documented_in
|
academic theses
challenge reports
|
|
gptkbp:is_evaluated_by
|
expert reviewers
accuracy and speed
|
|
gptkbp:is_funded_by
|
grants and sponsorships
|
|
gptkbp:is_influential_in
|
development of diagnostic tools
|
|
gptkbp:is_organized_by
|
gptkb:University_Medical_Center_Utrecht
|
|
gptkbp:is_part_of
|
gptkb:health_services
AI competitions
AI challenges in medicine
medical imaging challenges
|
|
gptkbp:is_prominent_in
|
computer vision research
|
|
gptkbp:is_promoted_by
|
healthcare organizations
|
|
gptkbp:is_recognized_by
|
medical research community
|
|
gptkbp:is_related_to
|
breast cancer detection
|
|
gptkbp:is_supported_by
|
non-profit organizations
various academic institutions
|
|
gptkbp:is_used_for
|
benchmarking algorithms
|
|
gptkbp:objective
|
evaluate algorithms for detecting metastases in lymph node sections
|
|
gptkbp:outcome
|
advancements in cancer research
|
|
gptkbp:participating_nations
|
international teams
|
|
gptkbp:presented_by
|
conferences
|
|
gptkbp:promotes
|
machine learning in pathology
|
|
gptkbp:provides
|
public access to data
|
|
gptkbp:provides_information_on
|
Camelyon16 dataset
|
|
gptkbp:utilizes
|
deep learning techniques
|
|
gptkbp:bfsParent
|
gptkb:Camelyon17
|
|
gptkbp:bfsLayer
|
10
|