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Artificial Intelligence in Radiation Oncology: A Specialty-wide Disruptive Transformation?

In the field of Radiation Oncology, clinical decision support has at least three main applications:

  1. The pre-planning prediction of dosimetric tradeoffs to assist physicians, patients and payers alike to make better informed decisions about treatment modality and dose prescription.
  2. The integration of dosimetric information with orthogonal data (e.g. genomics, imaging, EMR) to build accurate outcomes models of Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP).
  3. Radiomics, which is a branch of medical imaging analytics that relies upon primary extraction of quantitative imaging features (e.g. texture) to predict various clinical phenomena.

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