FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4307498511> ?p ?o ?g. }

• W4307498511 endingPage "514" @default.
• W4307498511 startingPage "504" @default.
• W4307498511 abstract "As two important textual modalities in electronic health records (EHR), both structured data (clinical codes) and unstructured data (clinical narratives) have recently been increasingly applied to the healthcare domain. Most existing EHR-oriented studies, however, either focus on a particular modality or integrate data from different modalities in a straightforward manner, which usually treats structured and unstructured data as two independent sources of information about patient admission and ignore the intrinsic interactions between them. In fact, the two modalities are documented during the same encounter where structured data inform the documentation of unstructured data and vice versa. In this paper, we proposed a Medical Multimodal Pre-trained Language Model, named MedM-PLM, to learn enhanced EHR representations over structured and unstructured data and explore the interaction of two modalities. In MedM-PLM, two Transformer-based neural network components are firstly adopted to learn representative characteristics from each modality. A cross-modal module is then introduced to model their interactions. We pre-trained MedM-PLM on the MIMIC-III dataset and verified the effectiveness of the model on three downstream clinical tasks, i.e., medication recommendation, 30-day readmission prediction and ICD coding. Extensive experiments demonstrate the power of MedM-PLM compared with state-of-the-art methods. Further analyses and visualizations show the robustness of our model, which could potentially provide more comprehensive interpretations for clinical decision-making." @default.
• W4307498511 created "2022-11-02" @default.
• W4307498511 creator A5014238603 @default.
• W4307498511 creator A5034348483 @default.
• W4307498511 creator A5065358136 @default.
• W4307498511 creator A5066028215 @default.
• W4307498511 creator A5077536816 @default.
• W4307498511 creator A5081083643 @default.
• W4307498511 creator A5089747719 @default.
• W4307498511 creator A5090366405 @default.
• W4307498511 date "2023-01-01" @default.
• W4307498511 modified "2023-10-16" @default.
• W4307498511 title "Multimodal Data Matters: Language Model Pre-Training Over Structured and Unstructured Electronic Health Records" @default.
• W4307498511 cites W1541250240 @default.
• W4307498511 cites W169580636 @default.
• W4307498511 cites W2004910511 @default.
• W4307498511 cites W2012487908 @default.
• W4307498511 cites W2014676531 @default.
• W4307498511 cites W2020214980 @default.
• W4307498511 cites W2027867013 @default.
• W4307498511 cites W2050091824 @default.
• W4307498511 cites W2110242546 @default.
• W4307498511 cites W2115441252 @default.
• W4307498511 cites W2168041406 @default.
• W4307498511 cites W2283041611 @default.
• W4307498511 cites W2395172628 @default.
• W4307498511 cites W2404901863 @default.
• W4307498511 cites W2443172870 @default.
• W4307498511 cites W2511950764 @default.
• W4307498511 cites W2517388783 @default.
• W4307498511 cites W2557074642 @default.
• W4307498511 cites W2625625371 @default.
• W4307498511 cites W2745238137 @default.
• W4307498511 cites W2748645708 @default.
• W4307498511 cites W2797082239 @default.
• W4307498511 cites W2804604520 @default.
• W4307498511 cites W2808915113 @default.
• W4307498511 cites W2905810301 @default.
• W4307498511 cites W2906103632 @default.
• W4307498511 cites W2907646605 @default.
• W4307498511 cites W2911489562 @default.
• W4307498511 cites W2914241418 @default.
• W4307498511 cites W2947607756 @default.
• W4307498511 cites W2964142373 @default.
• W4307498511 cites W2964758338 @default.
• W4307498511 cites W2965570621 @default.
• W4307498511 cites W2985621057 @default.
• W4307498511 cites W2997353686 @default.
• W4307498511 cites W2997494090 @default.
• W4307498511 cites W2998314166 @default.
• W4307498511 cites W3005285779 @default.
• W4307498511 cites W3006913750 @default.
• W4307498511 cites W3015173574 @default.
• W4307498511 cites W3017637887 @default.
• W4307498511 cites W3027889410 @default.
• W4307498511 cites W3036836886 @default.
• W4307498511 cites W3098724294 @default.
• W4307498511 cites W3098949126 @default.
• W4307498511 cites W3099750501 @default.
• W4307498511 cites W3101973032 @default.
• W4307498511 cites W3103901889 @default.
• W4307498511 cites W3107335993 @default.
• W4307498511 cites W3136047647 @default.
• W4307498511 cites W3136253378 @default.
• W4307498511 cites W3156998516 @default.
• W4307498511 cites W3160137267 @default.
• W4307498511 cites W3160359732 @default.
• W4307498511 cites W4205464244 @default.
• W4307498511 cites W4206042814 @default.
• W4307498511 doi "https://doi.org/10.1109/jbhi.2022.3217810" @default.
• W4307498511 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36306302" @default.
• W4307498511 hasPublicationYear "2023" @default.
• W4307498511 type Work @default.
• W4307498511 citedByCount "4" @default.
• W4307498511 countsByYear W43074985112023 @default.
• W4307498511 crossrefType "journal-article" @default.
• W4307498511 hasAuthorship W4307498511A5014238603 @default.
• W4307498511 hasAuthorship W4307498511A5034348483 @default.
• W4307498511 hasAuthorship W4307498511A5065358136 @default.
• W4307498511 hasAuthorship W4307498511A5066028215 @default.
• W4307498511 hasAuthorship W4307498511A5077536816 @default.
• W4307498511 hasAuthorship W4307498511A5081083643 @default.
• W4307498511 hasAuthorship W4307498511A5089747719 @default.
• W4307498511 hasAuthorship W4307498511A5090366405 @default.
• W4307498511 hasBestOaLocation W43074985112 @default.
• W4307498511 hasConcept C104317684 @default.
• W4307498511 hasConcept C119857082 @default.
• W4307498511 hasConcept C124101348 @default.
• W4307498511 hasConcept C144024400 @default.
• W4307498511 hasConcept C154945302 @default.
• W4307498511 hasConcept C185592680 @default.
• W4307498511 hasConcept C199360897 @default.
• W4307498511 hasConcept C204321447 @default.
• W4307498511 hasConcept C23123220 @default.
• W4307498511 hasConcept C2779903281 @default.
• W4307498511 hasConcept C2780226545 @default.
• W4307498511 hasConcept C2781252014 @default.
• W4307498511 hasConcept C36289849 @default.

• next