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Istituto sull'inquinamento atmosferico

Torna all'elenco Contributi in rivista anno 2017

Contributo in rivista

Tipo: Articolo in rivista

Titolo: An overview of the use of artificial neural networks in lung cancer research

Anno di pubblicazione: 2017

Formato: Elettronico Cartaceo

Autori: Bertolaccini, Luca; Solli, Piergiorgio; Pardolesi, Alessandro; Pasini, Antonello

Affiliazioni autori: AUSL Romagna Teaching Hospital; AUSL della Romagna; CNR-Institute of Atmospheric Pollution Research, Rome

Autori CNR:

  • ANTONELLO PASINI

Lingua: inglese

Abstract: The artificial neural networks (ANNs) are statistical models where the mathematical structure reproduces the biological organisation of neural cells simulating the learning dynamics of the brain. Although definitions of the term ANN could vary, the term usually refers to a neural network used for non-linear statistical data modelling. The neural models applied today in various fields of medicine, such as oncology, do not aim to be biologically realistic in detail but just efficient models for nonlinear regression or classification. ANN inference has applications in tasks that require attention focusing. ANNs also have a niche to carve in clinical decision support, but their success depends crucially on better integration with clinical protocols, together with an awareness of the need to combine different paradigms to produce the simplest and most transparent overall reasoning structure, and the will to evaluate this in a real clinical environment. We have performed an assessment of the evidence for improvements in the use of ANN in lung cancer research. Our analysis showed that often the use of ANN in the medical literature had not been performed in an accurate manner. A strict cooperation between physician and biostatisticians could be helpful in determine and resolve these errors.

Lingua abstract: inglese

Pagine da: 924

Pagine a: 931

Rivista:

Journal of thoracic disease Pioneer Bioscience Publishing Company
Paese di pubblicazione: Hong Kong
Lingua: inglese
ISSN: 2072-1439

Numero volume: 9

Numero fascicolo: 4

DOI: 10.21037/jtd.2017.03.157

Referee: Sė: Internazionale

Stato della pubblicazione: Published version

Indicizzato da: Scopus [2-s2.0-85018686378]

Parole chiave:

  • Artificial neural networks (ANNs)
  • Biostatistics
  • Lung cancer

URL: http://www.scopus.com/record/display.url?eid=2-s2.0-85018686378&origin=inward

Data di accettazione: 13/03/2017

Strutture CNR:

 
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