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Clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Lippincott Williams & Wilkins
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9276375/ https://www.ncbi.nlm.nih.gov/pubmed/35471478 http://dx.doi.org/10.1097/CM9.0000000000002002 |
| _version_ | 1784745711061958656 |
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| author | Lv, Han Li, Mengyi Wang, Zhenchang Yang, Dawei Xu, Hui Li, Juan Liu, Yang Cao, Di Liu, Yawen Wu, Xinru Jin, He Zhang, Peng Zhao, Liqin Bai, Rixing Yue, Yunlong Li, Bin Zhang, Nengwei Zou, Mingzhu Song, Jinghai Yu, Weibin Zhang, Pin Tang, Weijun Yao, Qiyuan Liu, Liheng Yang, Hui Yang, Zhenghan Zhang, Zhongtao |
| author_facet | Lv, Han Li, Mengyi Wang, Zhenchang Yang, Dawei Xu, Hui Li, Juan Liu, Yang Cao, Di Liu, Yawen Wu, Xinru Jin, He Zhang, Peng Zhao, Liqin Bai, Rixing Yue, Yunlong Li, Bin Zhang, Nengwei Zou, Mingzhu Song, Jinghai Yu, Weibin Zhang, Pin Tang, Weijun Yao, Qiyuan Liu, Liheng Yang, Hui Yang, Zhenghan Zhang, Zhongtao |
| author_sort | Lv, Han |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-9276375 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2022 |
| publisher | Lippincott Williams & Wilkins |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-92763752022-07-13 Clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence Lv, Han Li, Mengyi Wang, Zhenchang Yang, Dawei Xu, Hui Li, Juan Liu, Yang Cao, Di Liu, Yawen Wu, Xinru Jin, He Zhang, Peng Zhao, Liqin Bai, Rixing Yue, Yunlong Li, Bin Zhang, Nengwei Zou, Mingzhu Song, Jinghai Yu, Weibin Zhang, Pin Tang, Weijun Yao, Qiyuan Liu, Liheng Yang, Hui Yang, Zhenghan Zhang, Zhongtao Chin Med J (Engl) Consensus Statement Lippincott Williams & Wilkins 2022-03-20 2022-03-03 /pmc/articles/PMC9276375/ /pubmed/35471478 http://dx.doi.org/10.1097/CM9.0000000000002002 Text en Copyright © 2022 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
| spellingShingle | Consensus Statement Lv, Han Li, Mengyi Wang, Zhenchang Yang, Dawei Xu, Hui Li, Juan Liu, Yang Cao, Di Liu, Yawen Wu, Xinru Jin, He Zhang, Peng Zhao, Liqin Bai, Rixing Yue, Yunlong Li, Bin Zhang, Nengwei Zou, Mingzhu Song, Jinghai Yu, Weibin Zhang, Pin Tang, Weijun Yao, Qiyuan Liu, Liheng Yang, Hui Yang, Zhenghan Zhang, Zhongtao Clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence |
| title | Clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence |
| title_full | Clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence |
| title_fullStr | Clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence |
| title_full_unstemmed | Clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence |
| title_short | Clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence |
| title_sort | clinical practice guideline for body composition assessment based on upper abdominal magnetic resonance images annotated using artificial intelligence |
| topic | Consensus Statement |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9276375/ https://www.ncbi.nlm.nih.gov/pubmed/35471478 http://dx.doi.org/10.1097/CM9.0000000000002002 |
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