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Journal Abstract Search

1090 related items for PubMed ID: 34653224

  • 1. Text mining-based word representations for biomedical data analysis and protein-protein interaction networks in machine learning tasks.
    Alachram H, Chereda H, Beißbarth T, Wingender E, Stegmaier P.
    PLoS One; 2021; 16(10):e0258623. PubMed ID: 34653224
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  • 4. Unsupervised low-dimensional vector representations for words, phrases and text that are transparent, scalable, and produce similarity metrics that are not redundant with neural embeddings.
    Smalheiser NR, Cohen AM, Bonifield G.
    J Biomed Inform; 2019 Feb; 90():103096. PubMed ID: 30654030
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  • 6. A comparison of word embeddings for the biomedical natural language processing.
    Wang Y, Liu S, Afzal N, Rastegar-Mojarad M, Wang L, Shen F, Kingsbury P, Liu H.
    J Biomed Inform; 2018 Nov; 87():12-20. PubMed ID: 30217670
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  • 7. FuseLinker: Leveraging LLM's pre-trained text embeddings and domain knowledge to enhance GNN-based link prediction on biomedical knowledge graphs.
    Xiao Y, Zhang S, Zhou H, Li M, Yang H, Zhang R.
    J Biomed Inform; 2024 Oct; 158():104730. PubMed ID: 39326691
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  • 9. A hybrid model based on neural networks for biomedical relation extraction.
    Zhang Y, Lin H, Yang Z, Wang J, Zhang S, Sun Y, Yang L.
    J Biomed Inform; 2018 May; 81():83-92. PubMed ID: 29601989
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  • 10. Unsupervised and self-supervised deep learning approaches for biomedical text mining.
    Nadif M, Role F.
    Brief Bioinform; 2021 Mar 22; 22(2):1592-1603. PubMed ID: 33569575
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  • 11. Use of word and graph embedding to measure semantic relatedness between Unified Medical Language System concepts.
    Mao Y, Fung KW.
    J Am Med Inform Assoc; 2020 Oct 01; 27(10):1538-1546. PubMed ID: 33029614
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  • 12. Optimizing Word Embeddings for Patient Portal Message Datasets with a Small Number of Samples.
    Song Q, Ni C, Warner JL, Chen Q, Song L, Rosenbloom ST, Malin BA, Yin Z.
    Res Sq; 2024 May 15. PubMed ID: 38798621
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  • 13. An adverse drug effect mentions extraction method based on weighted online recurrent extreme learning machine.
    El-Allaly ED, Sarrouti M, En-Nahnahi N, Ouatik El Alaoui S.
    Comput Methods Programs Biomed; 2019 Jul 15; 176():33-41. PubMed ID: 31200909
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  • 14. Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network.
    Wu Y, Jiang M, Lei J, Xu H.
    Stud Health Technol Inform; 2015 Jul 15; 216():624-8. PubMed ID: 26262126
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  • 15. Anc2vec: embedding gene ontology terms by preserving ancestors relationships.
    Edera AA, Milone DH, Stegmayer G.
    Brief Bioinform; 2022 Mar 10; 23(2):. PubMed ID: 35136916
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  • 16. Comparative analysis on Facebook post interaction using DNN, ELM and LSTM.
    Khan SA, Chang HT.
    PLoS One; 2019 Mar 10; 14(11):e0224452. PubMed ID: 31714918
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  • 17. Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer.
    Chereda H, Bleckmann A, Menck K, Perera-Bel J, Stegmaier P, Auer F, Kramer F, Leha A, Beißbarth T.
    Genome Med; 2021 Mar 11; 13(1):42. PubMed ID: 33706810
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  • 18. BioWordVec, improving biomedical word embeddings with subword information and MeSH.
    Zhang Y, Chen Q, Yang Z, Lin H, Lu Z.
    Sci Data; 2019 May 10; 6(1):52. PubMed ID: 31076572
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  • 19. deepBioWSD: effective deep neural word sense disambiguation of biomedical text data.
    Pesaranghader A, Matwin S, Sokolova M, Pesaranghader A.
    J Am Med Inform Assoc; 2019 May 01; 26(5):438-446. PubMed ID: 30811548
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  • 20. Automatic query generation using word embeddings for retrieving passages describing experimental methods.
    Aydın F, Hüsünbeyi ZM, Özgür A.
    Database (Oxford); 2017 May 01; 2017():. PubMed ID: 28077568
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