156 related articles for article (PubMed ID: 37703507)
21. Cluster-based histopathology phenotype representation learning by self-supervised multi-class-token hierarchical ViT.
Ye J; Kalra S; Miri MS
Sci Rep; 2024 Feb; 14(1):3202. PubMed ID: 38331955
[TBL] [Abstract][Full Text] [Related]
22. Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation.
Eldele E; Ragab M; Chen Z; Wu M; Kwoh CK; Li X
IEEE Trans Neural Syst Rehabil Eng; 2023 Feb; PP():. PubMed ID: 37022869
[TBL] [Abstract][Full Text] [Related]
23. Evaluation of Effectiveness of Self-Supervised Learning in Chest X-Ray Imaging to Reduce Annotated Images.
Imagawa K; Shiomoto K
J Imaging Inform Med; 2024 Mar; ():. PubMed ID: 38459399
[TBL] [Abstract][Full Text] [Related]
24. Self-supervised maize kernel classification and segmentation for embryo identification.
Dong D; Nagasubramanian K; Wang R; Frei UK; Jubery TZ; Lübberstedt T; Ganapathysubramanian B
Front Plant Sci; 2023; 14():1108355. PubMed ID: 37123832
[TBL] [Abstract][Full Text] [Related]
25. Comprehensive study of semi-supervised learning for DNA methylation-based supervised classification of central nervous system tumors.
Tran QT; Alom MZ; Orr BA
BMC Bioinformatics; 2022 Jun; 23(1):223. PubMed ID: 35676649
[TBL] [Abstract][Full Text] [Related]
26. FaxMatch: Multi-Curriculum Pseudo-Labeling for semi-supervised medical image classification.
Peng Z; Zhang D; Tian S; Wu W; Yu L; Zhou S; Huang S
Med Phys; 2023 May; 50(5):3210-3222. PubMed ID: 36779849
[TBL] [Abstract][Full Text] [Related]
27. Self-Supervised Learning of Graph Neural Networks: A Unified Review.
Xie Y; Xu Z; Zhang J; Wang Z; Ji S
IEEE Trans Pattern Anal Mach Intell; 2023 Feb; 45(2):2412-2429. PubMed ID: 35476575
[TBL] [Abstract][Full Text] [Related]
28. EndoViT: pretraining vision transformers on a large collection of endoscopic images.
Batić D; Holm F; Özsoy E; Czempiel T; Navab N
Int J Comput Assist Radiol Surg; 2024 Jun; 19(6):1085-1091. PubMed ID: 38570373
[TBL] [Abstract][Full Text] [Related]
29. Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images.
Yu G; Sun K; Xu C; Shi XH; Wu C; Xie T; Meng RQ; Meng XH; Wang KS; Xiao HM; Deng HW
Nat Commun; 2021 Nov; 12(1):6311. PubMed ID: 34728629
[TBL] [Abstract][Full Text] [Related]
30. A survey of the impact of self-supervised pretraining for diagnostic tasks in medical X-ray, CT, MRI, and ultrasound.
VanBerlo B; Hoey J; Wong A
BMC Med Imaging; 2024 Apr; 24(1):79. PubMed ID: 38580932
[TBL] [Abstract][Full Text] [Related]
31. A Cluster-then-label Semi-supervised Learning Approach for Pathology Image Classification.
Peikari M; Salama S; Nofech-Mozes S; Martel AL
Sci Rep; 2018 May; 8(1):7193. PubMed ID: 29739993
[TBL] [Abstract][Full Text] [Related]
32. Physics-Guided Dual Self-Supervised Learning for Structure-Based Material Property Prediction.
Fu N; Wei L; Hu J
J Phys Chem Lett; 2024 Mar; 15(10):2841-2850. PubMed ID: 38442260
[TBL] [Abstract][Full Text] [Related]
33. DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer.
Schirris Y; Gavves E; Nederlof I; Horlings HM; Teuwen J
Med Image Anal; 2022 Jul; 79():102464. PubMed ID: 35596966
[TBL] [Abstract][Full Text] [Related]
34. Self-supervised learning for medical image data with anatomy-oriented imaging planes.
Zhang T; Wei D; Zhu M; Gu S; Zheng Y
Med Image Anal; 2024 May; 94():103151. PubMed ID: 38527405
[TBL] [Abstract][Full Text] [Related]
35. Hierarchical discriminative learning improves visual representations of biomedical microscopy.
Jiang C; Hou X; Kondepudi A; Chowdury A; Freudiger CW; Orringer DA; Lee H; Hollon TC
Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit; 2023 Jun; 2023():19798-19808. PubMed ID: 37654477
[TBL] [Abstract][Full Text] [Related]
36. Semi-supervised Long-tail Endoscopic Image Classification.
Cao RN; Fang MJ; Li HL; Tian J; Dong D
Chin Med Sci J; 2022 Sep; 37(3):171-180. PubMed ID: 36321172
[TBL] [Abstract][Full Text] [Related]
37. Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.
Ghaffari Laleh N; Muti HS; Loeffler CML; Echle A; Saldanha OL; Mahmood F; Lu MY; Trautwein C; Langer R; Dislich B; Buelow RD; Grabsch HI; Brenner H; Chang-Claude J; Alwers E; Brinker TJ; Khader F; Truhn D; Gaisa NT; Boor P; Hoffmeister M; Schulz V; Kather JN
Med Image Anal; 2022 Jul; 79():102474. PubMed ID: 35588568
[TBL] [Abstract][Full Text] [Related]
38. A General-Purpose Self-Supervised Model for Computational Pathology.
Chen RJ; Ding T; Lu MY; Williamson DFK; Jaume G; Chen B; Zhang A; Shao D; Song AH; Shaban M; Williams M; Vaidya A; Sahai S; Oldenburg L; Weishaupt LL; Wang JJ; Williams W; Le LP; Gerber G; Mahmood F
ArXiv; 2023 Aug; ():. PubMed ID: 37693180
[TBL] [Abstract][Full Text] [Related]
39. CLIP knows image aesthetics.
Hentschel S; Kobs K; Hotho A
Front Artif Intell; 2022; 5():976235. PubMed ID: 36504688
[TBL] [Abstract][Full Text] [Related]
40. Uncovering the structure of clinical EEG signals with self-supervised learning.
Banville H; Chehab O; Hyvärinen A; Engemann DA; Gramfort A
J Neural Eng; 2021 Mar; 18(4):. PubMed ID: 33181507
[No Abstract] [Full Text] [Related]
[Previous] [Next] [New Search]