Cargando…
Can natural language processing help differentiate inflammatory intestinal diseases in China? Models applying random forest and convolutional neural network approaches
BACKGROUND: Differentiating between ulcerative colitis (UC), Crohn’s disease (CD) and intestinal tuberculosis (ITB) using endoscopy is challenging. We aimed to realize automatic differential diagnosis among these diseases through machine learning algorithms. METHODS: A total of 6399 consecutive pati...
Autores principales: | Tong, Yuanren, Lu, Keming, Yang, Yingyun, Li, Ji, Lin, Yucong, Wu, Dong, Yang, Aiming, Li, Yue, Yu, Sheng, Qian, Jiaming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7526202/ https://www.ncbi.nlm.nih.gov/pubmed/32993636 http://dx.doi.org/10.1186/s12911-020-01277-w |
Ejemplares similares
-
Building a trustworthy AI differential diagnosis application for Crohn’s disease and intestinal tuberculosis
por: Lu, Keming, et al.
Publicado: (2023) -
Convolutional neural network-based segmentation can help in assessing the substantia nigra in neuromelanin MRI
por: Le Berre, Alice, et al.
Publicado: (2019) -
Research on improved convolutional wavelet neural network
por: Liu, Jingwei, et al.
Publicado: (2021) -
Parameterizable Design on Convolutional Neural Networks Using Chisel Hardware Construction Language
por: Madineni, Mukesh Chowdary, et al.
Publicado: (2023) -
Hypertuned Deep Convolutional Neural Network for Sign Language Recognition
por: Mannan, Abdul, et al.
Publicado: (2022)