AIMC Topic: Neural Networks, Computer

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Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
The identification of drug-drug interactions (DDIs) is important for patient safety; yet, compared to other pharmacovigilance work, a limited amount of research has been conducted in this space. Recent work has successfully applied a method of derivi...
Algorithms Computational Biology Drug Interactions Drug-Related Side Effects and Adverse Reactions Models, Biological Humans Neural Networks, Computer Polypharmacy Pharmacovigilance Data Visualization Semantics
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Training a Convolutional Neural Network with Terminology Summarization Data Improves SNOMED CT Enrichment.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
As a step toward learning to automatically insert new concepts into a large biomedical ontology, we are studying the easier problem of automatically verifying that an IS-A link should exist between a new child concept and an existing parent concept. ...
Deep Learning Neural Networks, Computer Machine Learning Systematized Nomenclature of Medicine Biological Ontologies
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De-identification of Clinical Text via Bi-LSTM-CRF with Neural Language Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
De-identification of clinical text, the prerequisite of electronic clinical data reuse, is a typical named entity recogni tion (NER) problem. A number of state-of-the-art deep learning methods for NER, such as Bi-LSTM-CRF (bidirec tional long-short-t...
Deep Learning Natural Language Processing Data Anonymization Language Neural Networks, Computer
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Assessing Contribution of Higher Order Clinical Risk Factors to Prediction of Outcome in Aneurysmal Subarachnoid Hemorrhage Patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
The goal of this study was to investigate the application of machine learning models capable of capturing multiplica tive and temporal clinical risk factors for outcome prediction inpatients with aneurysmal subarachnoid hemorrhage (aSAH). We examined...
Humans Logistic Models Neural Networks, Computer Treatment Outcome Machine Learning Cohort Studies Prognosis Area Under Curve ROC Curve Risk Factors Subarachnoid Hemorrhage
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Comparing Deep Learning Models for Multi-cell Classification in Liquid- based Cervical Cytology Image.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Liquid-based cytology (LBC) is a reliable automated technique for the screening of Papanicolaou (Pap) smear data. It is an effective technique for collecting a majority of the cervical cells and aiding cytopathologists in locating abnormal cells. Mos...
Vaginal Smears Cervix Uteri Datasets as Topic Deep Learning ROC Curve Papanicolaou Test Female Uterine Cervical Neoplasms Humans Neural Networks, Computer
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A High Recall Classifier for Selecting Articles for MEDLINE Indexing.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
MEDLINE is the National Library of Medicine's premier bibliographic database for biomedical literature. A highly valuable feature of the database is that each record is manually indexed with a controlled vocabulary called MeSH. Most MEDLINE journals ...
National Library of Medicine (U.S.) MEDLINE Medical Subject Headings Machine Learning United States Neural Networks, Computer Abstracting and Indexing
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Bootstrapping Adversarial Learning of Biomedical Ontology Alignments.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Learning how to automatically align biomedical ontologies has been a long-standing goal, given their ever-growing content and the many applications that rely on them. Because the knowledge graphs underlying biomedical ontologies enable neural learnin...
Biological Ontologies Vocabulary, Controlled Models, Theoretical Semantics Neural Networks, Computer Machine Learning
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Predicting Transition Words Between Sentence for English and Spanish Medical Text.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Transition words add important information and are useful for increasing text comprehension for readers. Our goal is to automatically detect transition words in the medical domain. We introduce a new dataset for identifying transition words categoriz...
Humans Language Datasets as Topic Comprehension Neural Networks, Computer Writing Linguistics
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A Residual Based Attention Model for EEG Based Sleep Staging.

IEEE journal of biomedical and health informatics Mar 3, 2020
Sleep staging is to score the sleep state of a subject into different sleep stages such as Wake and Rapid Eye Movement (REM). It plays an indispensable role in the diagnosis and treatment of sleep disorders. As manual sleep staging through well-train...
Aged Young Adult Adult Databases, Factual Female Middle Aged Deep Learning Male Electroencephalography Signal Processing, Computer-Assisted Sleep Stages Humans Neural Networks, Computer
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Constructing large-scale cortical brain networks from scalp EEG with Bayesian nonnegative matrix factorization.

Neural networks : the official journal of the International Neural Network Society Mar 3, 2020
A large-scale network provides a high hierarchical level for understanding the adaptive adjustment of the human brain during cognition processes. Since high spatial resolution is required, most of the related works are based on functional magnetic re...
Electroencephalography Cerebral Cortex Neural Pathways Neural Networks, Computer Models, Neurological Bayes Theorem Humans
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