Can natural language processing help differentiate inflammatory intestinal diseases in China? Models applying random forest and convolutional neural network approaches - Tong, Yuanren; Lu, Keming; Yang, Yingyun; Li, Ji; Lin, Yucong; Wu, Dong; Yang, Aiming; Li, Yue; Yu, Sheng; Qian, Jiaming (BMC medical informatics and decision making, 2020)
Keywords: Algorithms; Artificial Intelligence; Artificial neural networks; China; Classifiers; Colon; Colonoscopy; Construction; Crohn's disease; Data mining; Data processing; Diagnosis, Differential; Differential diagnosis; Disease; Electronic health records; Endoscopy; Health Informatics; Hospitals; Humans; Image segmentation; India; Inflammatory bowel disease; Inflammatory bowel diseases; Inflammatory Bowel Diseases - diagnosis; Information Systems and Communication Service; Intestinal tuberculosis; Intestine; Learning algorithms; Machine learning; Management of Computing and Information Systems; Medical schools; Medicine; Medicine & Public Health; modeling; Models, Theoretical; Natural Language Processing; Neural networks; Neural Networks, Computer; Physicians; Predictive Value of Tests; Research Article; Sensitivity; technology; Tuberculosis; Tuberculosis, Gastrointestinal - diagnosis; Ulcerative colitis; Words (language); China; India; Inflammatory bowel disease; Natural language processing; Intestinal tuberculosis