A machine learning-based pulmonary venous obstruction prediction model using clinical data and CT image.
Zeyang YaoXinrong HuXiaobing LiuWen XieYuhao DongHailong QiuZewen ChenYiyu ShiXiaowei XuMeiping HuangJian ZhuangPublished in: Int. J. Comput. Assist. Radiol. Surg. (2021)
Keyphrases
- prediction model
- clinical data
- ct images
- cone beam
- machine learning
- ct scans
- medical data
- medical images
- computed tomography
- lung parenchyma
- knowledge discovery
- patient data
- statistical analysis
- regression model
- lymph nodes
- raw data
- neural network
- domain experts
- ct data
- clinical information
- decision trees
- mr images
- image reconstruction
- medical imaging
- knowledge acquisition
- computer tomography
- data mining
- learning algorithm
- cancer patients
- x ray
- image segmentation
- automated segmentation
- data sources
- medical records
- ground truth
- medical image analysis
- region of interest
- imaging modalities
- treatment planning
- domain knowledge
- pulmonary nodules
- radiation therapy
- three dimensional
- domain specific
- feature selection