Data mining in cancer research: Application nNotes

Paulo J G Lisboa, Alfredo Vellido, Roberto Tagliaferri, Francesco Napolitano, Michele Ceccarelli, Jose D. Martín-Guerrero, Elia Biganzoli

Research output: Contribution to journalArticle

34 Citations (Scopus)


Advances in cancer medicine have traditionally come from detailed understanding of biological processes, later translated into therapeutic interventions, whose effectiveness is established by rigorous analysis of clinical trials. Over the last two decades the increasing throughput of data from microarray screening, spectral imaging and longitudinal studies are turning the understanding of cancer pathology into as much a data-based as a biologically and clinically driven science, with potential to impact more strongly on evidence-based decision support moving towards personalized medicine [1].

Original languageEnglish
Article number5386112
Pages (from-to)14-18
Number of pages5
JournalIEEE Computational Intelligence Magazine
Issue number1
Publication statusPublished - 1 Feb 2010
Externally publishedYes


ASJC Scopus subject areas

  • Artificial Intelligence
  • Theoretical Computer Science

Cite this

Lisboa, P. J. G., Vellido, A., Tagliaferri, R., Napolitano, F., Ceccarelli, M., Martín-Guerrero, J. D., & Biganzoli, E. (2010). Data mining in cancer research: Application nNotes. IEEE Computational Intelligence Magazine, 5(1), 14-18. [5386112].