Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions.
Markus BrandJoel TroyaAdrian KrenzerZita SaßmannshausenWolfram G ZollerAlexander MeiningThomas J LuxAlexander HannPublished in: United European gastroenterology journal (2022)
Detection of endoscopic instruments in colonoscopy using artificial intelligence technology is reliable and achieves high sensitivity and specificity. Accordingly, the new convolutional neuronal network could be used to reduce distracting CADe detections during endoscopic procedures. Thus, our study demonstrates the great potential of artificial intelligence technology beyond mucosal assessment.
Keyphrases
- artificial intelligence
- deep learning
- machine learning
- big data
- ultrasound guided
- loop mediated isothermal amplification
- convolutional neural network
- real time pcr
- label free
- physical activity
- electronic health record
- endoscopic submucosal dissection
- social media
- human health
- blood brain barrier
- sensitive detection