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医学影像研究中的放射组学分析。

Radiomics analysis in medical imaging research.

机构信息

Department of Radiology, Mayo Clinic, Jacksonville, Florida, USA.

Center for Augmented Intelligence, Mayo Clinic, Jacksonville, Florida, USA.

出版信息

J Med Radiat Sci. 2023 Mar;70(1):3-7. doi: 10.1002/jmrs.662. Epub 2023 Feb 10.

DOI:10.1002/jmrs.662
PMID:36762402
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9977659/
Abstract

This article discusses the current research in the field of radiomics in medical imaging with emphasis on its role in fighting coronavirus disease 2019 (COVID-19). This article covers the building of radiomic models in a simple straightforward manner, while discussing radiomic models potential to help us face this pandemic.

摘要

本文讨论了医学影像领域中放射组学的当前研究，重点介绍了其在抗击 2019 年冠状病毒病（COVID-19）方面的作用。本文以简单直接的方式介绍了放射组学模型的构建，并讨论了放射组学模型帮助我们应对这一大流行病的潜力。

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[1]
Radiomics analysis in medical imaging research.

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[2]
Prediction of COVID-19 patients in danger of death using radiomic features of portable chest radiographs.

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[3]
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[4]
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[5]
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[6]
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[7]
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[9]
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[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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本文引用的文献

[1]
Criteria for the translation of radiomics into clinically useful tests.

Nat Rev Clin Oncol. 2023-2

[2]
Prediction of COVID-19 patients in danger of death using radiomic features of portable chest radiographs.

J Med Radiat Sci. 2023-3

[3]
Evaluation of the models generated from clinical features and deep learning-based segmentations: Can thoracic CT on admission help us to predict hospitalized COVID-19 patients who will require intensive care?

BMC Med Imaging. 2022-6-7

[4]
Radiomics/Radiogenomics in Lung Cancer: Basic Principles and Initial Clinical Results.

Cancers (Basel). 2022-3-25

[5]
Potential of the Non-Contrast-Enhanced Chest CT Radiomics to Distinguish Molecular Subtypes of Breast Cancer: A Retrospective Study.

Front Oncol. 2022-3-21

[6]
Tuning hyperparameters of machine learning algorithms and deep neural networks using metaheuristics: A bioinformatics study on biomedical and biological cases.

Comput Biol Chem. 2022-4

[7]
An automated COVID-19 triage pipeline using artificial intelligence based on chest radiographs and clinical data.

NPJ Digit Med. 2022-1-14

[8]
Texture analysis imaging "what a clinical radiologist needs to know".

Eur J Radiol. 2022-1

[9]
Radiomics for Survival Risk Stratification of Clinical and Pathologic Stage IA Pure-Solid Non-Small Cell Lung Cancer.

Radiology. 2022-2

[10]
CT-Based Radiomics Helps to Predict Residual Lung Lesions in COVID-19 Patients at Three Months after Discharge.

Diagnostics (Basel). 2021-9-30

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