This project encompasses the development of a novel end-to-end automated framework for literature extraction of machine learning applied in minimally invasive surgery by training the state-of-the-art Bidirectional Encoder Representations from Transformers (BERT) language model. A knowledge graph generated nodes and relationships through word embeddings and graph algorithms. Annotations were be made semi-autonomously and the system was designed as a web application to be readily deployed in a clinical setting. The proposed framework can be used as a diagnosis and procedural assistant or used to accelerate literature and systematic reviews.
Infos
Participants
- Vanier College
Année : 2021
Région : MONTREAL REGIONAL SCIENCE & TECHNOLOGY FAIR
Type de projet : E
Niveau scolaire : Collégial 1
École : Vanier College
Prix et distinctions
Finale Québécoise
MONTREAL REGIONAL SCIENCE & TECHNOLOGY FAIR
- Prix de l’Association Mathématique du Québec
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