Abstract
Driven by the growing demand of personalization of medical procedures, data-based, computer-aided cancer research in human patients is advancing at an accelerating pace, providing a broadening landscape of opportunity for Machine Learning methods. This landscape can be observed from the wide-reaching view of population studies down to the genotype detail. In this brief paper, we provide a sweeping glimpse, by no means exhaustive, of the state-of-the-art in this field at the different scales of data measurement and analysis.
| Original language | English |
|---|---|
| Title of host publication | ESANN 2008 Proceedings, 16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning |
| Pages | 55-64 |
| Number of pages | 10 |
| Publication status | Published - 2008 |
| Event | 16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, ESANN 2008 - Bruges, Belgium Duration: Apr 23 2008 → Apr 25 2008 |
Other
| Other | 16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, ESANN 2008 |
|---|---|
| Country | Belgium |
| City | Bruges |
| Period | 4/23/08 → 4/25/08 |
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ASJC Scopus subject areas
- Artificial Intelligence
- Information Systems
Cite this
Vellido, A., Biganzoli, E., & Lisboa, P. J. G. (2008). Machine learning in cancer research: Implications for personalised medicine. In ESANN 2008 Proceedings, 16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning (pp. 55-64)