These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
2. A deep learning image-based intrinsic molecular subtype classifier of breast tumors reveals tumor heterogeneity that may affect survival. Jaber MI; Song B; Taylor C; Vaske CJ; Benz SC; Rabizadeh S; Soon-Shiong P; Szeto CW Breast Cancer Res; 2020 Jan; 22(1):12. PubMed ID: 31992350 [TBL] [Abstract][Full Text] [Related]
3. BrcaSeg: A Deep Learning Approach for Tissue Quantification and Genomic Correlations of Histopathological Images. Lu Z; Zhan X; Wu Y; Cheng J; Shao W; Ni D; Han Z; Zhang J; Feng Q; Huang K Genomics Proteomics Bioinformatics; 2021 Dec; 19(6):1032-1042. PubMed ID: 34280546 [TBL] [Abstract][Full Text] [Related]
4. Deep learning features encode interpretable morphologies within histological images. Foroughi Pour A; White BS; Park J; Sheridan TB; Chuang JH Sci Rep; 2022 Jun; 12(1):9428. PubMed ID: 35676395 [TBL] [Abstract][Full Text] [Related]
6. Deep learning for colon cancer histopathological images analysis. Ben Hamida A; Devanne M; Weber J; Truntzer C; Derangère V; Ghiringhelli F; Forestier G; Wemmert C Comput Biol Med; 2021 Sep; 136():104730. PubMed ID: 34375901 [TBL] [Abstract][Full Text] [Related]
7. Deep-Hipo: Multi-scale receptive field deep learning for histopathological image analysis. Kosaraju SC; Hao J; Koh HM; Kang M Methods; 2020 Jul; 179():3-13. PubMed ID: 32442672 [TBL] [Abstract][Full Text] [Related]
8. Deep Learning Models for Histopathological Classification of Gastric and Colonic Epithelial Tumours. Iizuka O; Kanavati F; Kato K; Rambeau M; Arihiro K; Tsuneki M Sci Rep; 2020 Jan; 10(1):1504. PubMed ID: 32001752 [TBL] [Abstract][Full Text] [Related]
9. 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]
10. Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning. Jang HJ; Lee A; Kang J; Song IH; Lee SH World J Gastroenterol; 2020 Oct; 26(40):6207-6223. PubMed ID: 33177794 [TBL] [Abstract][Full Text] [Related]
11. Prediction of BRCA Gene Mutation in Breast Cancer Based on Deep Learning and Histopathology Images. Wang X; Zou C; Zhang Y; Li X; Wang C; Ke F; Chen J; Wang W; Wang D; Xu X; Xie L; Zhang Y Front Genet; 2021; 12():661109. PubMed ID: 34354733 [TBL] [Abstract][Full Text] [Related]
12. Spatially aware graph neural networks and cross-level molecular profile prediction in colon cancer histopathology: a retrospective multi-cohort study. Ding K; Zhou M; Wang H; Zhang S; Metaxas DN Lancet Digit Health; 2022 Nov; 4(11):e787-e795. PubMed ID: 36307192 [TBL] [Abstract][Full Text] [Related]
13. A novel deep learning-based algorithm combining histopathological features with tissue areas to predict colorectal cancer survival from whole-slide images. Li YJ; Chou HH; Lin PC; Shen MR; Hsieh SY J Transl Med; 2023 Oct; 21(1):731. PubMed ID: 37848862 [TBL] [Abstract][Full Text] [Related]
14. Patch-level Tumor Classification in Digital Histopathology Images with Domain Adapted Deep Learning. Xia T; Kumar A; Feng D; Kim J Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():644-647. PubMed ID: 30440479 [TBL] [Abstract][Full Text] [Related]
15. Deep learning image analysis quantifies tumor heterogeneity and identifies microsatellite instability in colon cancer. Rubinstein JC; Foroughi Pour A; Zhou J; Sheridan TB; White BS; Chuang JH J Surg Oncol; 2023 Mar; 127(3):426-433. PubMed ID: 36251352 [TBL] [Abstract][Full Text] [Related]
16. A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks. Lagree A; Mohebpour M; Meti N; Saednia K; Lu FI; Slodkowska E; Gandhi S; Rakovitch E; Shenfield A; Sadeghi-Naini A; Tran WT Sci Rep; 2021 Apr; 11(1):8025. PubMed ID: 33850222 [TBL] [Abstract][Full Text] [Related]
17. High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection. Cruz-Roa A; Gilmore H; Basavanhally A; Feldman M; Ganesan S; Shih N; Tomaszewski J; Madabhushi A; González F PLoS One; 2018; 13(5):e0196828. PubMed ID: 29795581 [TBL] [Abstract][Full Text] [Related]
18. Deep learning trained on hematoxylin and eosin tumor region of Interest predicts HER2 status and trastuzumab treatment response in HER2+ breast cancer. Farahmand S; Fernandez AI; Ahmed FS; Rimm DL; Chuang JH; Reisenbichler E; Zarringhalam K Mod Pathol; 2022 Jan; 35(1):44-51. PubMed ID: 34493825 [TBL] [Abstract][Full Text] [Related]
19. Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers. Huang Y; Yao Z; Li L; Mao R; Huang W; Hu Z; Hu Y; Wang Y; Guo R; Tang X; Yang L; Wang Y; Luo R; Yu J; Zhou J EBioMedicine; 2023 Aug; 94():104706. PubMed ID: 37478528 [TBL] [Abstract][Full Text] [Related]
20. Using hybrid pre-trained models for breast cancer detection. Zarif S; Abdulkader H; Elaraby I; Alharbi A; Elkilani WS; Pławiak P PLoS One; 2024; 19(1):e0296912. PubMed ID: 38252633 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]