Application of artificial intelligence radiomics in the diagnosis, treatment, and prognosis of hepatocellular carcinoma
Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved..
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, with an increasing incidence and poor prognosis. In the past decade, artificial intelligence (AI) technology has undergone rapid development in the field of clinical medicine, bringing the advantages of efficient data processing and accurate model construction. Promisingly, AI-based radiomics has played an increasingly important role in the clinical decision-making of HCC patients, providing new technical guarantees for prediction, diagnosis, and prognostication. In this review, we evaluated the current landscape of AI radiomics in the management of HCC, including its diagnosis, individual treatment, and survival prognosis. Furthermore, we discussed remaining challenges and future perspectives regarding the application of AI radiomics in HCC.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:173 |
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| Enthalten in: |
Computers in biology and medicine - 173(2024) vom: 08. Apr., Seite 108337 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Bo, Zhiyuan [VerfasserIn] |
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| Links: |
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| Themen: |
Artificial intelligence |
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| Anmerkungen: |
Date Completed 17.04.2024 Date Revised 17.04.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.compbiomed.2024.108337 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM370371852 |
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| 520 | |a Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved. | ||
| 520 | |a Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, with an increasing incidence and poor prognosis. In the past decade, artificial intelligence (AI) technology has undergone rapid development in the field of clinical medicine, bringing the advantages of efficient data processing and accurate model construction. Promisingly, AI-based radiomics has played an increasingly important role in the clinical decision-making of HCC patients, providing new technical guarantees for prediction, diagnosis, and prognostication. In this review, we evaluated the current landscape of AI radiomics in the management of HCC, including its diagnosis, individual treatment, and survival prognosis. Furthermore, we discussed remaining challenges and future perspectives regarding the application of AI radiomics in HCC | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Review | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Hepatocellular carcinoma | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a Precision medicine | |
| 650 | 4 | |a Radiomics | |
| 700 | 1 | |a Song, Jiatao |e verfasserin |4 aut | |
| 700 | 1 | |a He, Qikuan |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Bo |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Ziyan |e verfasserin |4 aut | |
| 700 | 1 | |a Xie, Xiaozai |e verfasserin |4 aut | |
| 700 | 1 | |a Shu, Danyang |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Kaiyu |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yi |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Gang |e verfasserin |4 aut | |
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