BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

367 related articles for article (PubMed ID: 35596966)

  • 41. Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification.
    Chitnis SR; Liu S; Dash T; Verlekar TT; Di Ieva A; Berkovsky S; Vig L; Srinivasan A
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083343
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Self-supervised contrastive learning with random walks for medical image segmentation with limited annotations.
    Fischer M; Hepp T; Gatidis S; Yang B
    Comput Med Imaging Graph; 2023 Mar; 104():102174. PubMed ID: 36640485
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Deep learning identifies morphological patterns of homologous recombination deficiency in luminal breast cancers from whole slide images.
    Lazard T; Bataillon G; Naylor P; Popova T; Bidard FC; Stoppa-Lyonnet D; Stern MH; Decencière E; Walter T; Vincent-Salomon A
    Cell Rep Med; 2022 Dec; 3(12):100872. PubMed ID: 36516847
    [TBL] [Abstract][Full Text] [Related]  

  • 44. LESS: Label-efficient multi-scale learning for cytological whole slide image screening.
    Zhao B; Deng W; Li ZHH; Zhou C; Gao Z; Wang G; Li X
    Med Image Anal; 2024 May; 94():103109. PubMed ID: 38387243
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Self-supervised clustering analysis of colorectal cancer biomarkers based on multi-scale whole slides image and mass spectrometry imaging fused images.
    Li Z; Sun Y; An F; Chen H; Liao J
    Talanta; 2023 Oct; 263():124727. PubMed ID: 37247451
    [TBL] [Abstract][Full Text] [Related]  

  • 46. 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]  

  • 47. Contrastive learning-based histopathological features infer molecular subtypes and clinical outcomes of breast cancer from unannotated whole slide images.
    Liu H; Zhang Y; Luo J
    Comput Biol Med; 2024 Mar; 170():107997. PubMed ID: 38271839
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Deep learning detects genetic alterations in cancer histology generated by adversarial networks.
    Krause J; Grabsch HI; Kloor M; Jendrusch M; Echle A; Buelow RD; Boor P; Luedde T; Brinker TJ; Trautwein C; Pearson AT; Quirke P; Jenniskens J; Offermans K; van den Brandt PA; Kather JN
    J Pathol; 2021 May; 254(1):70-79. PubMed ID: 33565124
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study.
    Loeffler CML; El Nahhas OSM; Muti HS; Seibel T; Cifci D; van Treeck M; Gustav M; Carrero ZI; Gaisa NT; Lehmann KV; Leary A; Selenica P; Reis-Filho JS; Bruechle NO; Kather JN
    medRxiv; 2023 Mar; ():. PubMed ID: 36945540
    [TBL] [Abstract][Full Text] [Related]  

  • 50. MS-CLAM: Mixed supervision for the classification and localization of tumors in Whole Slide Images.
    Tourniaire P; Ilie M; Hofman P; Ayache N; Delingette H
    Med Image Anal; 2023 Apr; 85():102763. PubMed ID: 36764037
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Self-Distilled Supervised Contrastive Learning for diagnosis of breast cancers with histopathological images.
    Gong R; Wang L; Wang J; Ge B; Yu H; Shi J
    Comput Biol Med; 2022 Jul; 146():105641. PubMed ID: 35617728
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer.
    Zamanitajeddin N; Jahanifar M; Bilal M; Eastwood M; Rajpoot N
    Med Image Anal; 2024 Apr; 93():103071. PubMed ID: 38199068
    [TBL] [Abstract][Full Text] [Related]  

  • 53. A semi-supervised multi-task learning framework for cancer classification with weak annotation in whole-slide images.
    Gao Z; Hong B; Li Y; Zhang X; Wu J; Wang C; Zhang X; Gong T; Zheng Y; Meng D; Li C
    Med Image Anal; 2023 Jan; 83():102652. PubMed ID: 36327654
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Masked autoencoders with handcrafted feature predictions: Transformer for weakly supervised esophageal cancer classification.
    Bai Y; Li W; An J; Xia L; Chen H; Zhao G; Gao Z
    Comput Methods Programs Biomed; 2024 Feb; 244():107936. PubMed ID: 38016392
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Use of Deep Learning to Develop and Analyze Computational Hematoxylin and Eosin Staining of Prostate Core Biopsy Images for Tumor Diagnosis.
    Rana A; Lowe A; Lithgow M; Horback K; Janovitz T; Da Silva A; Tsai H; Shanmugam V; Bayat A; Shah P
    JAMA Netw Open; 2020 May; 3(5):e205111. PubMed ID: 32432709
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Classification of colorectal cancer consensus molecular subtypes using attention-based multi-instance learning network on whole-slide images.
    Xu H; Wu A; Ren H; Yu C; Liu G; Liu L
    Acta Histochem; 2023 Aug; 125(6):152057. PubMed ID: 37300984
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Contrastive Self-Supervised Pre-Training for Video Quality Assessment.
    Chen P; Li L; Wu J; Dong W; Shi G
    IEEE Trans Image Process; 2022; 31():458-471. PubMed ID: 34874856
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Prototypical multiple instance learning for predicting lymph node metastasis of breast cancer from whole-slide pathological images.
    Yu JG; Wu Z; Ming Y; Deng S; Li Y; Ou C; He C; Wang B; Zhang P; Wang Y
    Med Image Anal; 2023 Apr; 85():102748. PubMed ID: 36731274
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Efficient quality control of whole slide pathology images with human-in-the-loop training.
    Patil A; Diwakar H; Sawant J; Kurian NC; Yadav S; Rane S; Bameta T; Sethi A
    J Pathol Inform; 2023; 14():100306. PubMed ID: 37089617
    [TBL] [Abstract][Full Text] [Related]  

  • 60. [A region-level contrastive learning-based deep model for glomerular ultrastructure segmentation on electron microscope images].
    Lin G; Zhang Z; Lu Y; Geng J; Zhou Z; Lu L; Cao L
    Nan Fang Yi Ke Da Xue Xue Bao; 2023 May; 43(5):815-824. PubMed ID: 37313824
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 19.