Literature DB >> 12148816

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

Gian Paolo Drago1, Ernesto Setti, Lisa Licitra, Diego Liberati.   

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.

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Year:  2002        PMID: 12148816     DOI: 10.1109/TBME.2002.800788

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  3 in total

1.  An artificial neural network improves prediction of observed survival in patients with laryngeal squamous carcinoma.

Authors:  Andrew S Jones; Azzam G F Taktak; Timothy R Helliwell; John E Fenton; Martin A Birchall; David J Husband; Anthony C Fisher
Journal:  Eur Arch Otorhinolaryngol       Date:  2006-05-05       Impact factor: 2.503

Review 2.  Machine Learning for Endometrial Cancer Prediction and Prognostication.

Authors:  Vipul Bhardwaj; Arundhiti Sharma; Snijesh Valiya Parambath; Ijaz Gul; Xi Zhang; Peter E Lobie; Peiwu Qin; Vijay Pandey
Journal:  Front Oncol       Date:  2022-07-27       Impact factor: 5.738

3.  Applications of machine learning in cancer prediction and prognosis.

Authors:  Joseph A Cruz; David S Wishart
Journal:  Cancer Inform       Date:  2007-02-11
  3 in total

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