Titel

Merkliste
1 Ergebnisse

3D deep learning versus the current methods for predicting ..:

Yilv Lv ; Ying Wei ; Kuan Xu...
https://www.frontiersin.org/articles/10.3389/fonc.2022.995870/full. , 2022

Link: https://doi.org/10.3389/fonc.2022.995870

RT Journal
T1 <Title>3D deep learning versus the current methods for predicting tumor invasiveness of lung adenocarcinoma based on high-resolution computed tomography images</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:7f1a5f8ad5ae43df9b243577fd4844f8&Exemplar=1&LAN=DE
				
A1 Yilv Lv
A1 Ying Wei
A1 Kuan Xu
A1 Xiaobin Zhang
A1 Rong Hua
A1 Jia Huang
A1 Min Li
A1 Cui Tang
A1 Long Yang
A1 Bingchun Liu
A1 Yonggang Yuan
A1 Siwen Li
A1 Yaozong Gao
A1 Xianjie Zhang
A1 Yifan Wu
A1 Yuchen Han
A1 Zhanxian Shang
A1 Hong Yu
A1 Yiqiang Zhan
A1 Feng Shi
A1 Bo Ye
PB Frontiers Media S.A.
YR 2022
K1 computer-aided diagnosis
K1 lung adenocarcinoma
K1 intraoperative frozen section
K1 tumor invasiveness
K1 artificial intelligence
K1 non-small cell lung (NSCLC)
K1 Neoplasms. Tumors. Oncology. Including cancer and carcinogens
K1 RC254-282
JF https://www.frontiersin.org/articles/10.3389/fonc.2022.995870/full
LK http://dx.doi.org/https://doi.org/10.3389/fonc.2022.995870
DO https://doi.org/10.3389/fonc.2022.995870
SF ELIB - SuUB Bremen

Export

RefWorks (nur Desktop-Version!)
Flow (Zuerst in Flow einloggen, dann importieren)