Practical considerations regarding classification learning for clinical diagnosis and therapy advice in oncology | Zendy

Flávio S. Corrêa da Silva | Zendy; Frederico Costa | Zendy; Antônio Francisco Iemma | Zendy

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Practical considerations regarding classification learning for clinical diagnosis and therapy advice in oncology

Author(s) -

Flávio S. Corrêa da Silva,

Frederico Costa,

Antônio Francisco Iemma

Publication year - 2020

Publication title -

ict express

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.733

H-Index - 22

ISSN - 2405-9595

DOI - 10.1016/j.icte.2020.03.004

Subject(s) - radiation therapy , advice (programming) , medicine , medical physics , clinical oncology , intensive care medicine , oncology , computer science , cancer , programming language

In the present article the relationship between machine learning and medicine is reviewed, in order to assess the potential for the practical use of machine learning for diagnosis and therapy advice. The considerations built herein are particularly suitable for oncology, in which early diagnostics is particularly important for the success of treatments, and therapy is often based on chemotherapy and radiotherapy, which have harmful side effects.

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