Radiomics and artificial intelligence for precision medicine in lung cancer treatment

Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human eye but can be captured non-invasively on medical imaging as radiomic features, which can form a high dimensional data space amenable to machine learning. Radiomic features can be harnessed and used in an artificial intelligence paradigm to risk stratify patients, and predict for histological and molecular findings, and clinical outcome measures, thereby facilitating precision medicine for improving patient care. Compared to tissue sampling-driven approaches, radiomics-based methods are superior for being non-invasive, reproducible,…

• NI
  National Institute for Health and Care Research
• AO
  Academy of Medical Sciences

  Award: SGL026\1024
• IC
  Imperial College Healthcare NHS Trust
• NI
  NIHR Imperial Biomedical Research Centre

  Awards: P62585, WSCC P87324