ARTIFICIAL INTELLIGENCE IN ONCOLOGY: APPLICATIONS, CHALLENGES, AND FUTURE DIRECTIONS

Modern medicine — and oncology in particular — is on the verge of integrating artificial intelligence (AI) into routine clinical practice. This article highlights some of the most successful initiatives showcasing how AI is being applied in diagnosing and predicting the progression of cancer. Existing clinical decision support systems that incorporate neural network-based oncology diagnostic modules are examined. For the first time, the limitations of AI applications in oncology are discussed, along with strategies to address these challenges.

Authors

Publication Details

Journal
Techscience.uz.
Published
2025-08-11
DOI
https://doi.org/10.47390/ts-v3i5y2025n1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

ARTIFICIAL INTELLIGENCE IN ONCOLOGY: APPLICATIONS, CHALLENGES, AND FUTURE DIRECTIONS

Sherzod Sobirov
Techscience.uz.
Radiomics and Machine Learning in Medical Imaging
article

ARTIFICIAL INTELLIGENCE IN ONCOLOGY: APPLICATIONS, CHALLENGES, AND FUTURE DIRECTIONS

Sherzod Sobirov
article en

Abstract

Modern medicine — and oncology in particular — is on the verge of integrating artificial intelligence (AI) into routine clinical practice. This article highlights some of the most successful initiatives showcasing how AI is being applied in diagnosing and predicting the progression of cancer. Existing clinical decision support systems that incorporate neural network-based oncology diagnostic modules are examined. For the first time, the limitations of AI applications in oncology are discussed, along with strategies to address these challenges.

Techscience.uz.Vol. 3(5)
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Openalex Percentile: Top 70%
Radiomics and Machine Learning in Medical Imaging
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ARTIFICIAL INTELLIGENCE IN ONCOLOGY: APPLICATIONS, CHALLENGES, AND FUTURE DIRECTIONS — Sherzod Sobirov · Techscience.uz. (2025) | TGRS Research Map | TGRS