Artificial intelligence in oncology: areas of application, prospects and limitations
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Keywords

artificial intelligence
early diagnosis
genetic markers
medical decision support systems

How to Cite

Kulbakin, D., Choinzonov, E., Tolmachev, I., Starikov, I., Starikova, E., & Kaverina, I. (2022). Artificial intelligence in oncology: areas of application, prospects and limitations. Voprosy Onkologii, 68(6), 691–699. https://doi.org/10.37469/0507-3758-2022-68-6-691-699

Abstract

Modern medicine and oncology, in particular, are one step away from the widespread introduction of artificial intelligence into everyday medical practice.

The article describes the most successful projects demonstrating involvement of artificial intelligence in diagnosis and prognosis of the course of oncological diseases.

The existing systems for making medical decisions, including diagnosing modules for oncological diseases based on neural networks, have been analyzed. Limitations for the use of artificial intelligence in oncology and ways to overcome them have been highlighted for the first time.

Artificial intelligence methods have proven their efficacy in image analysis (X-ray images, histological slides) and can be applied for supporting medical decision-making.

A huge array of accumulated knowledge about the molecular biological nature of tumors finds its practical application for prescribing treatment and predicting the course of the disease by means of machine learning algorithms.

Artificial intelligence can be the key to improving the efficacy of medical care provided for oncological diseases.

https://doi.org/10.37469/0507-3758-2022-68-6-691-699
##article.numberofdownloads## 724
##article.numberofviews## 876
pdf (Русский)

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