AIMC Journal:
Journal of biomedical informatics

Showing 301 to 310 of 650 articles

Cross domains adversarial learning for Chinese named entity recognition for online medical consultation.

Journal of biomedical informatics Oct 23, 2020
Deep learning methods have been applied to Chinese named entity recognition for the online medical consultation. They require a large number of marked samples. However, no such database is available at present. This paper begins with constructing a l...
Electronic Health Records Language China Natural Language Processing Referral and Consultation
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Concept placement using BERT trained by transforming and summarizing biomedical ontology structure.

Journal of biomedical informatics Oct 22, 2020
The comprehensive modeling and hierarchical positioning of a new concept in an ontology heavily relies on its set of proper subsumption relationships (IS-As) to other concepts. Identifying a concept's IS-A relationships is a laborious task requiring ...
Language Natural Language Processing Systematized Nomenclature of Medicine Biological Ontologies
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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...
Machine Learning Natural Language Processing Systematic Reviews as Topic Information Storage and Retrieval MEDLINE
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Sampling methods and feature selection for mortality prediction with neural networks.

Journal of biomedical informatics Oct 5, 2020
Along with digitization, automatic data-driven decision support systems become increasingly popular. Mortality prediction is a vital part of that decision process. With more data available, sophisticated machine learning models like (Artificial) Neur...
Neural Networks, Computer Machine Learning Reproducibility of Results Hospital Mortality ROC Curve
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Multi-Ontology Refined Embeddings (MORE): A hybrid multi-ontology and corpus-based semantic representation model for biomedical concepts.

Journal of biomedical informatics Oct 1, 2020
OBJECTIVE: Currently, a major limitation for natural language processing (NLP) analyses in clinical applications is that concepts are not effectively referenced in various forms across different texts. This paper introduces Multi-Ontology Refined Emb...
Humans Cluster Analysis Natural Language Processing Semantics Biological Ontologies Medical Subject Headings
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A deep learning-based, unsupervised method to impute missing values in electronic health records for improved patient management.

Journal of biomedical informatics Oct 1, 2020
Electronic health records (EHRs) often suffer missing values, for which recent advances in deep learning offer a promising remedy. We develop a deep learning-based, unsupervised method to impute missing values in patient records, then examine its imp...
Humans Research Design Electronic Health Records Deep Learning Data Accuracy
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Learning hidden patterns from patient multivariate time series data using convolutional neural networks: A case study of healthcare cost prediction.

Journal of biomedical informatics Sep 25, 2020
OBJECTIVE: To develop an effective and scalable individual-level patient cost prediction method by automatically learning hidden temporal patterns from multivariate time series data in patient insurance claims using a convolutional neural network (CN...
Humans Neural Networks, Computer Cohort Studies Health Care Costs
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Extracting and classifying diagnosis dates from clinical notes: A case study.

Journal of biomedical informatics Sep 16, 2020
Myeloproliferative neoplasms (MPNs) are chronic hematologic malignancies that may progress over long disease courses. The original date of diagnosis is an important piece of information for patient care and research, but is not consistently documente...
Humans Electronic Health Records Natural Language Processing
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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...
Humans Neural Networks, Computer Machine Learning Neoplasms Information Storage and Retrieval Computing Methodologies
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Creating a database for health IT events via a hybrid deep learning model.

Journal of biomedical informatics Sep 9, 2020
OBJECTIVE: The use of poorly designed and improperly implemented health information technology (HIT) may compound risks because it can disrupt established work patterns and encourage workarounds. Analyzing and learning from HIT events could reduce th...
Databases, Factual Deep Learning Research Report Medical Informatics Biomedical Technology
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