Open AccessIntelligent classification of breast cancer based on deep learning
Author(s) -
Yuhang Liao,
Yulan Peng,
Dongquan Liu,
Jingyan Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1827/1/012171
Subject(s) - breast cancer , artificial neural network , artificial intelligence , feature (linguistics) , computer science , deep learning , cancer , machine learning , medicine , linguistics , philosophy
How to use artificial intelligence to assist physicians in analyzing complex breast cancer medical data has become an urgent problem to be solved. From the perspective of auxiliary diagnosis, we propose a method to classify breast cancer grades by cases. Based on the Chinese electronic medical records of breast cancer provided by the Department of Ultrasound at West China Hospital, we compared neural network methods, including FASTTEXT, TEXTCNN, TEXTRNN. And proposed the N-LM-ATT model. N represents the n-gram feature, LM represents the Long Short-Term Memory (LSTM) network, and ATT represents the Attention Mechanism (AM). This article focuses on the classification of Chinese breast cancer text data based on natural language processing (NLP) method. By comparing the above methods, the N-LM-ATT model achieved the best performance on the breast cancer ultrasound dataset of West China Hospital.