Introduction: What is Machine Learning
Computational Learning Theory
Overview of Supervised Learning Methods
Overview of Unsupervised Learning Methods
Performance Evaluation
Variety of Applications in Radiation Oncology
Machine Learning for Quality Assurance: Quality Assurance as a Learning Problem
Detection of Radiotherapy Errors Using Unsupervised Learning
Prediction of Radiotherapy Errors Using Supervised Learning
Machine Learning for Computer-Aided Detection: Detection of Cancer Lesions from Imaging
Classification of Malignant and Benign Tumours
Machine Learning for Treatment Planning and Delivery
Image-guided Radiotherapy with Machine Learning: IMRT Optimization Using Machine Learning
Treatment Assessment Tools
Machine Learning for Motion Management: Prediction of Respiratory Motion
Motion-Correction Using Learning Methods
Machine Learning Application in 4D-CT
Machine Learning Application in Dynamic Delivery
Machine Learning for Outcomes Modeling: Bioinformatics of Treatment Response
Modelling of Norma Tissue Complication Probabilities (NTCP)
Modelling of Tumour Control Probability (TCP).