Use of word and graph embedding to measure semantic relatedness between Unified Medical Language System concepts
Số trang: 9
Loại file: pdf
Dung lượng: 478.61 KB
Lượt xem: 10
Lượt tải: 0
Xem trước 2 trang đầu tiên của tài liệu này:
Thông tin tài liệu:
The study sought to explore the use of deep learning techniques to measure the semantic relatedness between Unified Medical Language System (UMLS) concepts. Concept sentence embeddings were generated for UMLS concepts by applying the word embedding models BioWordVec and various flavors of BERT to concept sentences formed by concatenating UMLS terms.
Nội dung trích xuất từ tài liệu:
Use of word and graph embedding to measure semantic relatedness between Unified Medical Language System concepts
Nội dung trích xuất từ tài liệu:
Use of word and graph embedding to measure semantic relatedness between Unified Medical Language System concepts
Tìm kiếm theo từ khóa liên quan:
Medical informatics association Semantic relatedness Medical terminologies Deep learning Word embedding Graph embeddingGợi ý tài liệu liên quan:
-
8 trang 200 0 0
-
Application of convolutional neural network for detecting concrete cracks
4 trang 33 0 0 -
11 trang 31 0 0
-
Modern approaches in natural language processing
25 trang 31 0 0 -
Improving hand posture recognition performance using multi-modalities
10 trang 30 0 0 -
8 trang 29 0 0
-
91 trang 29 0 0
-
8 trang 28 0 0
-
Research on traffic congestion detection from camera images in a location of Da Lat
13 trang 27 0 0 -
Mô hình huấn luyện mạng nơ ron dựa trên ảnh mô phỏng
7 trang 23 0 0