Supervised learning (machine learning)
Supervised learning is the most common type of machine learning algorithm used in medical imaging research. It involves training an algorithm from a set of images or data where the output labels are already known ^{1}.
Supervised learning is broken into two subcategories, classification and regression ^{2}. Classification refers to the prediction of whether an image falls into one or more categories while regression aims to predict a continuous label. Medical imaging machine learning deals mainly with the classification of images.
Fundamentally, the optimisation of supervised machine learning consists of two phases that are looped through continuously ^{3}:
 forward propagation: for a given input, calculates a predicted outcome and compares this with the expected outcome to give an overall cost (error)
 backward propagation: from the cost, works backwards through the network updating the parameters in an attempt to minimise the overall cost
Radiology example
 simplified, a given input, (such as a lung nodule ROI) calculates the predicted outcome over the expected outcome once the cost is estimated the network will update the individual weighting of the output parameters (think of it as a vote)
 the output parameters that correctly identified the nodule to the expected outcome are awarded a heavier 'vote'
 the output parameters that did not correctly identified the nodule to the expected outcome are adjusted to minimise cost
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Machine learning

artificial intelligence (AI)
 computer aided diagnosis (CAD)

machine learning (overview)
 types of machine learning
 models
 linear regression
 logistic regression
 decision tree
 random forest
 support vector machine
 neural network (overview)
 common data preparation/preprocessing steps
 DICOM to bitmap
 scaling/centering
 normalisation
 principal component analysis
 train/test/validation split
 augmentation
 loss functions
 mean squared error
 cross entropy
 optimisation algorithms
 stochastic gradient descent
 momentum (Nesterov)
 ADAM
 regularisation
 linear and quadratic
 batch normalization

ensembling
 boosting
 bagging
 rulebased expert systems
 glossary