Cargando…
Machine learning based gray-level co-occurrence matrix early warning system enables accurate detection of colorectal cancer pelvic bone metastases on MRI
OBJECTIVE: The mortality of colorectal cancer patients with pelvic bone metastasis is imminent, and timely diagnosis and intervention to improve the prognosis is particularly important. Therefore, this study aimed to build a bone metastasis prediction model based on Gray level Co-occurrence Matrix (...
Autores principales: | Jin, Jinlian, Zhou, Haiyan, Sun, Shulin, Tian, Zhe, Ren, Haibing, Feng, Jinwu, Jiang, Xinping |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073745/ https://www.ncbi.nlm.nih.gov/pubmed/37035167 http://dx.doi.org/10.3389/fonc.2023.1121594 |
Ejemplares similares
-
Supervised Learning Based Systemic Inflammatory Markers Enable Accurate Additional Surgery for pT1NxM0 Colorectal Cancer: A Comparative Analysis of Two Practical Prediction Models for Lymph Node Metastasis
por: Jin, Jinlian, et al.
Publicado: (2021) -
CT/MRI of nodal metastases in pelvic cancer
por: Husband, Janet E.
Publicado: (2015) -
Gray level co-occurrence matrix and extreme learning machine for Covid-19 diagnosis
por: Pi, Pengpeng, et al.
Publicado: (2021) -
Machine learning based early warning system enables accurate mortality risk prediction for COVID-19
por: Gao, Yue, et al.
Publicado: (2020) -
Analysis of gear surface morphology based on gray level co-occurrence matrix and fractal dimension
por: Wei, Bo, et al.
Publicado: (2019)