Radiomics and Radiogenomics Platforms Integrating Machine Learning Techniques: A Review

被引：0

作者：

Oliveira, Rafael ^{[1
]}

Martinho, Beatriz ^{[1
]}

Vieiral, Ana ^{[1
]}

Rocha, Nelson Pacheco ^{[2
]}

机构：

[1] Univ Aveiro, Dept Med Sci, Aveiro, Portugal

[2] Univ Aveiro, Dept Med Sci, IEETA, Aveiro, Portugal

来源：

INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 3, WORLDCIST 2023 | 2024年 / 801卷

关键词：

Radiomics; Radiogenomics; Machine Learning; Oncology; Medical Imaging; Precision Medicine; CANCER;

D O I：

10.1007/978-3-031-45648-0_42

中图分类号：

学科分类号：

摘要：

Radiomics and radiogenomics are still new fields to be explored in oncology, although there are several platforms and tools already developed, or in development. This review aimed to identify the current state of the art of radiomics and radiogenomics in terms of platforms and tools integrating machine learning techniques to support the analysis of medical imaging studies of oncological patients. A systematic literature search was performed, and 19 studies were included in the review. These studies were published between 2016 and 2022 and considered several platforms and tools integrating machine learning techniques for the analysis of medical imaging studies of oncological patients together with molecular and clinical endpoints. However, the included articles present scarce evidence related to the translation of the reported platforms and tools to the clinical practice.

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页码：429 / 438

页数：10

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