Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 16 of 16 for “"Biomedical Domain"”.
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From Hidden Data and Information towards Data-Driven Research in the Biomedical Domain
… However, data-driven research, especially in the biomedical domain, is hampered by several aspects. While literature data is freely available to researchers, it is neither machine-readable nor easy to find, given the enormous growth of electronic data. On the other hand, although medical data is …
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Studying The Effectiveness Of Large Language Models In Benchmark Biomedical Tasks
… work has investigated their capability in the biomedical domain yet. To this end, this thesis aims to evaluate the performance of LLMs on benchmark biomedical tasks. For this purpose, a comprehensive evaluation of 4 popular LLMs in 6 diverse biomedical tasks across 26 datasets has been …
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Robust Entity Linking in Heterogeneous Domains
… Linking systems were optimized for specific domains (e.g., general domain, biomedical domain), knowledge base types (e.g., DBpedia, Wikipedia), or document structures (e.g., tables) and types (e.g., news articles, tweets). This led to very specialized systems that lack robustness and are only …
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Word sense disambiguation in clinical text
… meanings, is pervasive in language of all domains. Word sense disambiguation (WSD) and word sense induction (WSI) are the tasks of resolving this ambiguity. Applications in the clinical and biomedical domain focus on the potential disambiguation has for information extraction. Most …
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Leveraging Structure and Knowledge in Clinical and Biomedical Representation Learning
… the machine learning for health and biomedicine domain are often noisy, irregularly sampled, only sparsely labeled, and small relative to the dimensionality of the both the data and the tasks. These problems motivate the use of representation learning in this domain, which encompasses a variety …
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Evolutionary approaches for feature selection in biological data
… area is finding interesting biomarkers from biomedical data. Mass throughput data generated from microarrays and mass spectrometry from biological samples are high dimensional and is small in sample size. Examples include DNA microarray datasets with up to 500,000 genes and mass spectrometry …
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Joint Biomedical Event Extraction and Entity Linking via Iterative Collaborative Training
Biomedical entity linking and event extraction are two crucial tasks to support text understanding and retrieval in the biomedical domain. These two tasks intrinsically benefit each other: entity linking disambiguates the biomedical concepts by referring to external knowledge bases and the domain …
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Advanced Methods for Entity Linking in the Life Sciences
… annotation process is applicable in different domains. Nevertheless, there is a difference between generic and specialized domains according to the annotation process. This thesis emphasizes the differences between the domains and addresses the identified challenges. The majority of annotation …
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Natural Language Processing Solutions for Knowledge Extraction: NetME and EmotWion
… PhD I used these methodologies in two different domains, biomedical knowledge networks building and analysis of the contagion of emotions in social networks. In biomedical domain, with the increasing volume and unstructured nature of scientific literature most of the information embedded within …
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Neural Word Representations for Biomedical NLP
… with a particular emphasis on the biomedical domain which is linguistically highly challenging. We focus on three directions: first, we present a comprehensive study on how the quality of the representation model varies according to its training parameters. For this, we implement a …
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Evaluation of Word and Paragraph Embeddings and Analogical Reasoning as an Alternative to Term Frequency-Inverse Document Frequency-based Classification in Support of Biocuration
… upper limit to precision and recall in a biomedical text classification task (F1-score of 0.85). Arguably, one could use ontologies to supplement TF-IDF, but ontologies are sparse in coverage and costly to create. This prompts a correlated question: can unsupervised learning capture …
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Mining Complex High-Order Datasets
… relatively absent from the literature within the biomedical domain. Furthermore, naive tensor approaches suffer from fundamental efficiency problems which limit their practical use in large-scale high-order mining and do not capture local neighborhoods necessary for accurate spatiotemporal …
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Automatically identifying facet roles from comparative structures to support biomedical text summarization
Within the context of biomedical scholarly articles, comparison sentences represent a rhetorical structure commonly used to communicate findings. More generally, comparison sentences are rich with information about how the properties of one or more entities relate one another. So far, in the …
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Active Expert Sourcing; Knowledge Extraction from Domain Specific Information
… important when adapting the algorithms to new domains. However, domain specific information imposes different challenges on NERs, such as the need for annotating a different set of Named Entity (NE) types (e.g. NE schema) or, more importantly, the need for domain expert annotators. Many domain …
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A modular, open-source information extraction framework for identifying clinical concepts and processes of care in clinical narratives
… patterns and the use of external domain knowledge resources to tackle a variety of information extraction tasks in the clinical domain, such as recognition of clinical concepts, events, temporal relations, term disambiguation and abbreviation expansion. Methods are developed for …
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Unsupervised Relation Extraction for E-Learning Applications
… regarding the important concepts present in a domain by relying on unsupervised relation extraction approaches as extracted semantic relations allow us to identify key information in a sentence. The extracted patterns (semantic relations) are then automatically transformed into questions. In …