156 related articles for article (PubMed ID: 37071058)
1. Deep learning-based classification and spatial prognosis risk score on whole-slide images of lung adenocarcinoma.
Ding H; Feng Y; Huang X; Xu J; Zhang T; Liang Y; Wang H; Chen B; Mao Q; Xia W; Huang X; Xu L; Dong G; Jiang F
Histopathology; 2023 Aug; 83(2):211-228. PubMed ID: 37071058
[TBL] [Abstract][Full Text] [Related]
2. Deep learning-based diagnosis of histopathological patterns for invasive non-mucinous lung adenocarcinoma using semantic segmentation.
Zhao Y; He S; Zhao D; Ju M; Zhen C; Dong Y; Zhang C; Wang L; Wang S; Che N
BMJ Open; 2023 Jul; 13(7):e069181. PubMed ID: 37491086
[TBL] [Abstract][Full Text] [Related]
3. Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks.
Wei JW; Tafe LJ; Linnik YA; Vaickus LJ; Tomita N; Hassanpour S
Sci Rep; 2019 Mar; 9(1):3358. PubMed ID: 30833650
[TBL] [Abstract][Full Text] [Related]
4. Deep learning-based six-type classifier for lung cancer and mimics from histopathological whole slide images: a retrospective study.
Yang H; Chen L; Cheng Z; Yang M; Wang J; Lin C; Wang Y; Huang L; Chen Y; Peng S; Ke Z; Li W
BMC Med; 2021 Mar; 19(1):80. PubMed ID: 33775248
[TBL] [Abstract][Full Text] [Related]
5. A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.
Gong J; Liu J; Hao W; Nie S; Zheng B; Wang S; Peng W
Eur Radiol; 2020 Apr; 30(4):1847-1855. PubMed ID: 31811427
[TBL] [Abstract][Full Text] [Related]
6. Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma.
Zhu Y; Chen LL; Luo YW; Zhang L; Ma HY; Yang HS; Liu BC; Li LJ; Zhang WB; Li XM; Xie CM; Yang JC; Wang DL; Li Q
Eur Radiol; 2023 Dec; 33(12):8542-8553. PubMed ID: 37436506
[TBL] [Abstract][Full Text] [Related]
7. Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.
Sadhwani A; Chang HW; Behrooz A; Brown T; Auvigne-Flament I; Patel H; Findlater R; Velez V; Tan F; Tekiela K; Wulczyn E; Yi ES; Mermel CH; Hanks D; Chen PC; Kulig K; Batenchuk C; Steiner DF; Cimermancic P
Sci Rep; 2021 Aug; 11(1):16605. PubMed ID: 34400666
[TBL] [Abstract][Full Text] [Related]
8. New vision of HookEfficientNet deep neural network: Intelligent histopathological recognition system of non-small cell lung cancer.
Yuan H; Kido T; Hirata M; Ueno K; Imai Y; Chen K; Ren W; Yang L; Chen K; Qu L; Wu Y
Comput Biol Med; 2024 Jun; 178():108710. PubMed ID: 38843570
[TBL] [Abstract][Full Text] [Related]
9. A collaborative workflow between pathologists and deep learning for the evaluation of tumour cellularity in lung adenocarcinoma.
Sakamoto T; Furukawa T; Pham HHN; Kuroda K; Tabata K; Kashima Y; Okoshi EN; Morimoto S; Bychkov A; Fukuoka J
Histopathology; 2022 Dec; 81(6):758-769. PubMed ID: 35989443
[TBL] [Abstract][Full Text] [Related]
10. Artificial intelligence-based recurrence prediction outperforms classical histopathological methods in pulmonary adenocarcinoma biopsies.
Akram F; Wolf JL; Trandafir TE; Dingemans AC; Stubbs AP; von der Thüsen JH
Lung Cancer; 2023 Dec; 186():107413. PubMed ID: 37939498
[TBL] [Abstract][Full Text] [Related]
11. Predictions of the dysregulated competing endogenous RNA signature involved in the progression of human lung adenocarcinoma.
Yang D; He Y; Wu B; Liu R; Wang N; Wang T; Luo Y; Li Y; Liu Y
Cancer Biomark; 2020; 29(3):399-416. PubMed ID: 32741804
[TBL] [Abstract][Full Text] [Related]
12. Tailoring pretext tasks to improve self-supervised learning in histopathologic subtype classification of lung adenocarcinomas.
Ding R; Yadav A; Rodriguez E; Araujo Lemos da Silva AC; Hsu W
Comput Biol Med; 2023 Nov; 166():107484. PubMed ID: 37741228
[TBL] [Abstract][Full Text] [Related]
13. Development and validation of a robust immune-related prognostic signature in early-stage lung adenocarcinoma.
Wu P; Zheng Y; Wang Y; Wang Y; Liang N
J Transl Med; 2020 Oct; 18(1):380. PubMed ID: 33028329
[TBL] [Abstract][Full Text] [Related]
14. ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network.
Wang S; Wang T; Yang L; Yang DM; Fujimoto J; Yi F; Luo X; Yang Y; Yao B; Lin S; Moran C; Kalhor N; Weissferdt A; Minna J; Xie Y; Wistuba II; Mao Y; Xiao G
EBioMedicine; 2019 Dec; 50():103-110. PubMed ID: 31767541
[TBL] [Abstract][Full Text] [Related]
15. Standardized Classification of Lung Adenocarcinoma Subtypes and Improvement of Grading Assessment Through Deep Learning.
Lami K; Ota N; Yamaoka S; Bychkov A; Matsumoto K; Uegami W; Munkhdelger J; Seki K; Sukhbaatar O; Attanoos R; Berezowska S; Brcic L; Cavazza A; English JC; Fabro AT; Ishida K; Kashima Y; Kitamura Y; Larsen BT; Marchevsky AM; Miyazaki T; Morimoto S; Ozasa M; Roden AC; Schneider F; Smith ML; Tabata K; Takano AM; Tanaka T; Tsuchiya T; Nagayasu T; Sakanashi H; Fukuoka J
Am J Pathol; 2023 Dec; 193(12):2066-2079. PubMed ID: 37544502
[TBL] [Abstract][Full Text] [Related]
16. A promising deep learning-assistive algorithm for histopathological screening of colorectal cancer.
Ho C; Zhao Z; Chen XF; Sauer J; Saraf SA; Jialdasani R; Taghipour K; Sathe A; Khor LY; Lim KH; Leow WQ
Sci Rep; 2022 Feb; 12(1):2222. PubMed ID: 35140318
[TBL] [Abstract][Full Text] [Related]
17. Convolutional neural networks can accurately distinguish four histologic growth patterns of lung adenocarcinoma in digital slides.
Gertych A; Swiderska-Chadaj Z; Ma Z; Ing N; Markiewicz T; Cierniak S; Salemi H; Guzman S; Walts AE; Knudsen BS
Sci Rep; 2019 Feb; 9(1):1483. PubMed ID: 30728398
[TBL] [Abstract][Full Text] [Related]
18. Deep learning-enhanced radiomics for histologic classification and grade stratification of stage IA lung adenocarcinoma: a multicenter study.
Pei G; Wang D; Sun K; Yang Y; Tang W; Sun Y; Yin S; Liu Q; Wang S; Huang Y
Front Oncol; 2023; 13():1224455. PubMed ID: 37546407
[TBL] [Abstract][Full Text] [Related]
19. Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning.
Coudray N; Ocampo PS; Sakellaropoulos T; Narula N; Snuderl M; Fenyö D; Moreira AL; Razavian N; Tsirigos A
Nat Med; 2018 Oct; 24(10):1559-1567. PubMed ID: 30224757
[TBL] [Abstract][Full Text] [Related]
20. Establishment of artificial intelligence model for precise histological subtyping of lung adenocarcinoma and its application to quantitative and spatial analysis.
Miura E; Emoto K; Abe T; Hashiguchi A; Hishida T; Asakura K; Sakamoto M
Jpn J Clin Oncol; 2024 May; ():. PubMed ID: 38757929
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
