AIMC Topic: Electronic Health Records

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Natural language processing and String Metric-assisted Assessment of Semantic Heterogeneity method for capturing and standardizing unstructured nursing activities in a hospital setting: a retrospective study.

Annali di igiene : medicina preventiva e di comunita Apr 12, 2022
BACKGROUND: Nurses record data in electronic health records (EHRs) using different terminologies and coding systems. The purpose of this study was to identify unstructured free-text nursing activities recorded by nurses in EHRs with natural language ...
Natural Language Processing Retrospective Studies Humans Electronic Health Records Semantics Reproducibility of Results Hospitals
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Online Disease Identification and Diagnosis and Treatment Based on Machine Learning Technology.

Journal of healthcare engineering Apr 12, 2022
The article uses machine learning algorithms to extract disease symptom keyword vectors. At the same time, we used deep learning technology to design a disease symptom classification model. We apply this model to an online disease consultation recomm...
Technology Electronic Health Records Algorithms Delivery of Health Care Humans Machine Learning
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Fusion of fully integrated analog machine learning classifier with electronic medical records for real-time prediction of sepsis onset.

Scientific reports Apr 5, 2022
The objective of this work is to develop a fusion artificial intelligence (AI) model that combines patient electronic medical record (EMR) and physiological sensor data to accurately predict early risk of sepsis. The fusion AI model has two component...
Humans Sepsis Artificial Intelligence Vital Signs Machine Learning Electronic Health Records
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Visualization of medical concepts represented using word embeddings: a scoping review.

BMC medical informatics and decision making Mar 29, 2022
BACKGROUND: Analyzing the unstructured textual data contained in electronic health records (EHRs) has always been a challenging task. Word embedding methods have become an essential foundation for neural network-based approaches in natural language p...
PubMed Semantics Electronic Health Records Natural Language Processing Humans Databases, Factual
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Information Extraction From Electronic Health Records to Predict Readmission Following Acute Myocardial Infarction: Does Natural Language Processing Using Clinical Notes Improve Prediction of Readmission?

Journal of the American Heart Association Mar 24, 2022
Background Social risk factors influence rehospitalization rates yet are challenging to incorporate into prediction models. Integration of social risk factors using natural language processing (NLP) and machine learning could improve risk prediction ...
Myocardial Infarction Medicare Patient Readmission Information Storage and Retrieval United States Natural Language Processing Electronic Health Records Aged Humans Retrospective Studies
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Chinese clinical named entity recognition via multi-head self-attention based BiLSTM-CRF.

Artificial intelligence in medicine Mar 18, 2022
Clinical named entity recognition (CNER) is a fundamental step for many clinical Natural Language Processing (NLP) systems, which aims to recognize and classify clinical entities such as diseases, symptoms, exams, body parts and treatments in clinica...
Electronic Health Records Language China Natural Language Processing Neural Networks, Computer
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Deep learning-based methods for natural hazard named entity recognition.

Scientific reports Mar 17, 2022
Natural hazard named entity recognition is a technique used to recognize natural hazard entities from a large number of texts. The method of natural hazard named entity recognition can facilitate acquisition of natural hazards information and provide...
Deep Learning Natural Language Processing Electronic Health Records Language Data Collection Names
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Temporal information extraction with the scalable cross-sentence context for electronic health records.

Journal of biomedical informatics Mar 15, 2022
Temporal information is essential for accurate understanding of medical information hidden in electronic health record texts. In the absence of temporal information, it is even impossible to distinguish whether the mentioned symptom is a current cond...
Algorithms Electronic Health Records Time Natural Language Processing Information Storage and Retrieval
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Design and Evaluation of a Postpartum Depression Ontology.

Applied clinical informatics Mar 9, 2022
OBJECTIVE: Postpartum depression (PPD) remains an understudied research area despite its high prevalence. The goal of this study is to develop an ontology to aid in the identification of patients with PPD and to enable future analyses with electronic...
Depression, Postpartum Prevalence Female Biological Ontologies Risk Factors Humans Electronic Health Records
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Clinical Text Data Categorization and Feature Extraction Using Medical-Fissure Algorithm and Neg-Seq Algorithm.

Computational intelligence and neuroscience Mar 7, 2022
A large amount of patient information has been gathered in Electronic Health Records (EHRs) concerning their conditions. An EHR, as an unstructured text document, serves to maintain health by identifying, treating, and curing illnesses. In this resea...
Natural Language Processing Data Accuracy Algorithms Electronic Health Records Humans Machine Learning
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