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Forecasting the performance status of head and neck cancer patient treatment by an interval arithmetic pruned perceptron

Academic Article
Publication Date:
2002
abstract:
The integration of chemotherapy and radiotherapy for the treatment of advanced head and neck cancer is still a matter of clinical investigation. An important limitation is that the concomitant administration of chemotherapy and radiotherapy still induces severe toxicity. In this paper, a simple artificial neural network is used to predict, on the basis of biological and clinical data, if the cumulative toxicity of the combined chemo-radiation treatment itself would be tolerated. The resulting method, tested on clinical data from a phase II trial, proved to be able to forecast which patients will tolerate a combined chemo-radiotherapeutic approach. This result should open a new perspective in the clinical approach, by supplying a potential predictive indicator for toxicity.
Iris type:
01.01 Articolo in rivista
Keywords:
interval arithmetic; learning; neural networks; perceptrons; predictive factors
List of contributors:
Drago, Giampaolo; Liberati, Diego
Authors of the University:
LIBERATI DIEGO
Handle:
https://iris.cnr.it/handle/20.500.14243/49162
Published in:
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Journal
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