Models (machine learning)

Each machine learning model will vary whilst being determined in part by the type of problem being solved. Although much of the recent work in the field of image processing generally, and more specifically radiology, has focused on convolutional neural networks, a type of neural network, a number of other models are useful in various circumstances. These include:

• linear regression
• logistic regression
• decision tree
• random forest
• support vector machines
• clustering models

Related Radiopaedia articles

Artificial intelligence

• artificial intelligence (AI)
• imaging data sets
• computer-aided diagnosis (CAD)
• natural language processing
• machine learning (overview)
  • machine learning processes
    • supervised learning
    • unsupervised learning
      • clustering
    • reinforcement learning
    • evolutionary algorithms
    • validation split
  • machine learning models
    • linear regression
    • logistic regression
    • decision tree
    • random forest
    • support vector machine
    • feature scaling
    • linear discriminant analysis
    • neural network (overview)
      • neural network architectures
        • ​fully-connected neural network
        • recurrent neural network
        • convolutional neural network
• visualizing and understanding neural networks
  • generative adversarial networks (GANs)
  • heat maps
  • class activation mapping(CAM)
• common data preparation/preprocessing steps
  • DICOM to bitmap conversion
  • dimensionality reduction 
  • scaling
  • centering
  • normalization
  • principal component analysis
  • training, testing and validation datasets
  • augmentation
  • loss function
    • mean squared error
    • cross entropy
  • optimization algorithms 
    • ADAM 
    • momentum (Nesterov)
    • stochastic gradient descent
    • mini-batch gradient descent
  • regularisation
    • linear and quadratic
    • batch normalization 
  • ensembling
    • boosting
    • bagging
  • rule-based expert systems
• glossary
  • activation function
  • anomaly detection
  • automation bias
  • backpropagation
  • batch size
  • computer vision
  • concept drift
  • cost function
  • confusion matrix
  • convolution
  • cross validation
  • curse of dimensionality
  • dice similarity coefficient
  • dimensionality reduction
  • epoch
  • explainable artificial intelligence/XAI
  • feature extraction
  • federated learning
  • gradient descent
  • ground truth
  • hyperparameters
  • image registration
  • imputation
  • iteration
  • jaccard index
  • linear algebra
  • noise reduction
  • normalization
  • R (Programming language)
  • Python (Programming language)
  • segmentation 
  • semi-supervised learning
  • synthetic and augmented data
  • overfitting
  • transfer learning