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Towards Parallel Algorithms for Abstract Dialectical Frameworks ...
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A theoretical and experimental analysis of BWT variants for string collections ...
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String Rearrangement Inequalities and a Total Order Between Primitive Words ...
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Dynamic Suffix Array with Polylogarithmic Queries and Updates ...
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Quantum Meets Fine-Grained Complexity: Sublinear Time Quantum Algorithms for String Problems ...
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An Optimal-Time RLBWT Construction in BWT-runs Bounded Space ...
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An Unsupervised Approach to Structuring and Analyzing Repetitive Semantic Structures in Free Text of Electronic Medical Records
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In: Journal of Personalized Medicine; Volume 12; Issue 1; Pages: 25 (2022)
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Abstract:
Electronic medical records (EMRs) include many valuable data about patients, which is, however, unstructured. Therefore, there is a lack of both labeled medical text data in Russian and tools for automatic annotation. As a result, today, it is hardly feasible for researchers to utilize text data of EMRs in training machine learning models in the biomedical domain. We present an unsupervised approach to medical data annotation. Syntactic trees are produced from initial sentences using morphological and syntactical analyses. In retrieved trees, similar subtrees are grouped using Node2Vec and Word2Vec and labeled using domain vocabularies and Wikidata categories. The usage of Wikidata categories increased the fraction of labeled sentences 5.5 times compared to labeling with domain vocabularies only. We show on a validation dataset that the proposed labeling method generates meaningful labels correctly for 92.7% of groups. Annotation with domain vocabularies and Wikidata categories covered more than 82% of sentences of the corpus, extended with timestamp and event labels 97% of sentences got covered. The obtained method can be used to label EMRs in Russian automatically. Additionally, the proposed methodology can be applied to other languages, which lack resources for automatic labeling and domain vocabulary.
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Keyword:
automatic text labeling; electronic health records; graph algorithms; natural language processing; Node2Vec; syntactical parsing
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URL: https://doi.org/10.3390/jpm12010025
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Optimal Fuzzy Controller Design for Autonomous Robot Path Tracking Using Population-Based Metaheuristics
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In: Symmetry; Volume 14; Issue 2; Pages: 202 (2022)
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Methods, Models and Tools for Improving the Quality of Textual Annotations
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In: Modelling; Volume 3; Issue 2; Pages: 224-242 (2022)
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Undecidability and Complexity for Super-Turing Models of Computation
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In: Proceedings; Volume 81; Issue 1; Pages: 123 (2022)
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Suffix tree-based linear algorithms for multiple prefixes, single suffix counting and listing problems ...
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Reduction ratio of the IS-algorithm: worst and random cases ...
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Optimal Fuzzy Controller Design for Autonomous Robot Path Tracking Using Population-Based Metaheuristics
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Design and development of a lead free piezoelectric energy harvester for wideband, low frequency and low amplitude vibrations
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In: Micromachines ; https://hal.archives-ouvertes.fr/hal-03549337 ; Micromachines, 2021, 12 (12), pp.1537 (2021)
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Distinct signatures of subjective confidence and objective accuracy in speech prosody
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In: ISSN: 0010-0277 ; EISSN: 1873-7838 ; Cognition ; https://hal.sorbonne-universite.fr/hal-03263512 ; Cognition, Elsevier, 2021, 212, pp.104661. ⟨10.1016/j.cognition.2021.104661⟩ (2021)
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E.W. Dijkstra, 1959, A Note on Two Problems in Connexion with Graphs. Numerische Mathematik 1, p. 269271 Version bilingue et commentée
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In: https://hal.archives-ouvertes.fr/hal-03171590 ; 2021 (2021)
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Critical Digital Humanities: texts, code and algorithms
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In: Humanités numériques dans et sur les Amériques ; https://hal.archives-ouvertes.fr/hal-03373785 ; Humanités numériques dans et sur les Amériques, Apr 2021, Avignon, France (2021)
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