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Artificial intelligence for precision oncology: beyond patient stratification.

Francisco Azuaje
Published in: NPJ precision oncology (2019)
The data-driven identification of disease states and treatment options is a crucial challenge for precision oncology. Artificial intelligence (AI) offers unique opportunities for enhancing such predictive capabilities in the lab and the clinic. AI, including its best-known branch of research, machine learning, has significant potential to enable precision oncology well beyond relatively well-known pattern recognition applications, such as the supervised classification of single-source omics or imaging datasets. This perspective highlights key advances and challenges in that direction. Furthermore, it argues that AI's scope and depth of research need to be expanded to achieve ground-breaking progress in precision oncology.
Keyphrases
  • artificial intelligence
  • machine learning
  • deep learning
  • big data
  • palliative care
  • primary care
  • high resolution
  • case report
  • optical coherence tomography
  • mass spectrometry
  • photodynamic therapy