AIMC Topic: Information Storage and Retrieval

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Using the contextual language model BERT for multi-criteria classification of scientific articles.

Journal of biomedical informatics Oct 13, 2020
BACKGROUND: Finding specific scientific articles in a large collection is an important natural language processing challenge in the biomedical domain. Systematic reviews and interactive article search are the type of downstream applications that bene...
Natural Language Processing Systematic Reviews as Topic Machine Learning Information Storage and Retrieval MEDLINE
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Unsupervised learning for large-scale corneal topography clustering.

Scientific reports Oct 12, 2020
Machine learning algorithms have recently shown their precision and potential in many different use cases and fields of medicine. Most of the algorithms used are supervised and need a large quantity of labeled data to achieve high accuracy. Also, mos...
Datasets as Topic Information Storage and Retrieval Corneal Topography Data Collection Corneal Diseases Databases, Factual Cluster Analysis Unsupervised Machine Learning Keratoconus Humans Algorithms
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Question-driven summarization of answers to consumer health questions.

Scientific data Oct 2, 2020
Automatic summarization of natural language is a widely studied area in computer science, one that is broadly applicable to anyone who needs to understand large quantities of information. In the medical domain, automatic summarization has the potenti...
Information Storage and Retrieval Consumer Health Informatics Natural Language Processing
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Korean clinical entity recognition from diagnosis text using BERT.

BMC medical informatics and decision making Sep 30, 2020
BACKGROUND: While clinical entity recognition mostly aims at electronic health records (EHRs), there are also the demands of dealing with the other type of text data. Automatic medical diagnosis is an example of new applications using a different dat...
Information Storage and Retrieval Republic of Korea Natural Language Processing Neural Networks, Computer Machine Learning Electronic Health Records Language Humans
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Biomedical document triage using a hierarchical attention-based capsule network.

BMC bioinformatics Sep 17, 2020
BACKGROUND: Biomedical document triage is the foundation of biomedical information extraction, which is important to precision medicine. Recently, some neural networks-based methods have been proposed to classify biomedical documents automatically. I...
Neural Networks, Computer Triage Information Storage and Retrieval Humans
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Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports.

Journal of biomedical informatics Sep 9, 2020
OBJECTIVE: In machine learning, it is evident that the classification of the task performance increases if bootstrap aggregation (bagging) is applied. However, the bagging of deep neural networks takes tremendous amounts of computational resources an...
Neoplasms Information Storage and Retrieval Neural Networks, Computer Machine Learning Computing Methodologies Humans
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A Year of Papers Using Biomedical Texts.

Yearbook of medical informatics Aug 21, 2020
OBJECTIVES: Analyze papers published in 2019 within the medical natural language processing (NLP) domain in order to select the best works of the field.
Data Mining Information Storage and Retrieval Electronic Health Records Natural Language Processing
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Medical Information Extraction in the Age of Deep Learning.

Yearbook of medical informatics Aug 21, 2020
OBJECTIVES: We survey recent developments in medical Information Extraction (IE) as reported in the literature from the past three years. Our focus is on the fundamental methodological paradigm shift from standard Machine Learning (ML) techniques to ...
Medical Informatics Disease Datasets as Topic Information Storage and Retrieval Humans Neural Networks, Computer Pharmaceutical Preparations Drug Interactions Deep Learning Natural Language Processing
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Hierarchical fusion of common sense knowledge and classifier decisions for answer selection in community question answering.

Neural networks : the official journal of the International Neural Network Society Aug 20, 2020
The goal of answer selection is to select the most applicable answers from an answer candidate pool. It plays an essential role in numerous applications in information retrieval (IR) and natural language processing (NLP). In this paper, we introduce ...
Information Storage and Retrieval Semantics Databases, Factual Natural Language Processing Humans Neural Networks, Computer
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Identifying disease trajectories with predicate information from a knowledge graph.

Journal of biomedical semantics Aug 20, 2020
BACKGROUND: Knowledge graphs can represent the contents of biomedical literature and databases as subject-predicate-object triples, thereby enabling comprehensive analyses that identify e.g. relationships between diseases. Some diseases are often dia...
Humans ROC Curve Information Storage and Retrieval Semantics Computer Graphics Biological Ontologies Disease
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