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Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications

Authors
 Yae Won Park  ;  Narae Lee  ;  Sung Soo Ahn  ;  Jong Hee Chang  ;  Seung-Koo Lee 
Citation
 Investigative Magnetic Resonance Imaging, Vol.25(4) : 266-280, 2021-12 
Journal Title
Investigative Magnetic Resonance Imaging
ISSN
 2384-1095 
Issue Date
2021-12
Keywords
Artificial intelligence ; Brain metastases ; Deep learning ; Machine learning ; Radiomics
Abstract
Advances in radiomics and deep learning (DL) hold great potential to be at the forefront of precision medicine for the treatment of patients with brain metastases. Radiomics and DL can aid clinical decision-making by enabling accurate diagnosis, facilitating the identification of molecular markers, providing accurate prognoses, and monitoring treatment response. In this review, we summarize the clinical background, unmet needs, and current state of research of radiomics and DL for the treatment of brain metastases. The promises, pitfalls, and future roadmap of radiomics and DL in brain metastases are addressed as well.
Files in This Item:
T202126263.pdf Download
DOI
10.13104/imri.2021.25.4.266
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurosurgery (신경외과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Park, Yae Won(박예원) ORCID logo https://orcid.org/0000-0001-8907-5401
Ahn, Sung Soo(안성수) ORCID logo https://orcid.org/0000-0002-0503-5558
Lee, Seung Koo(이승구) ORCID logo https://orcid.org/0000-0001-5646-4072
Chang, Jong Hee(장종희) ORCID logo https://orcid.org/0000-0003-1509-9800
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/190669
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