AIMC Topic: Electronic Health Records

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Evaluation of clinical named entity recognition methods for Serbian electronic health records.

International journal of medical informatics May 25, 2022
BACKGROUND AND OBJECTIVES: The importance of clinical natural language processing (NLP) has increased with the adoption of electronic health records (EHRs). One of the critical tasks in clinical NLP is named entity recognition (NER). Clinical NER in ...
Serbia Machine Learning Electronic Health Records Natural Language Processing Humans Neural Networks, Computer
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Systematic review of current natural language processing methods and applications in cardiology.

Heart (British Cardiac Society) May 25, 2022
Natural language processing (NLP) is a set of automated methods to organise and evaluate the information contained in unstructured clinical notes, which are a rich source of real-world data from clinical care that may be used to improve outcomes and ...
Humans Natural Language Processing Cardiology Algorithms Electronic Health Records
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Facilitating clinical research through automation: Combining optical character recognition with natural language processing.

Clinical trials (London, England) May 24, 2022
BACKGROUND/AIMS: Performance status is crucial for most clinical research, as an eligibility criterion, a comorbidity covariate, or a trial endpoint. Yet information on performance status often is embedded as free text within a patient's electronic m...
Information Storage and Retrieval Electronic Health Records Automation Clinical Trials as Topic Natural Language Processing Humans Software
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Digital Health Profile of South Korea: A Cross Sectional Study.

International journal of environmental research and public health May 23, 2022
(1) Backgroud: For future national digital healthcare policy development, it is vital to collect baseline data on the infrastructure and services of medical institutions' information and communication technology (ICT). To assess the state of medical ...
Electronic Health Records Republic of Korea Cross-Sectional Studies Hospitals, General Artificial Intelligence
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Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records.

Journal of neurodevelopmental disorders May 23, 2022
BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyp...
Natural Language Processing Vocabulary Autism Spectrum Disorder Electronic Health Records Phenotype Humans
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All-cause mortality prediction in T2D patients with iTirps.

Artificial intelligence in medicine May 21, 2022
Mortality in the type II diabetic elderly population can sometimes be prevented through intervention, for which risk assessment through predictive modeling is required. Since Electronic Health Records data are typically heterogeneous and sparse, the ...
Aged Humans Diabetes Mellitus, Type 2 Neural Networks, Computer Electronic Health Records
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Deep learning on time series laboratory test results from electronic health records for early detection of pancreatic cancer.

Journal of biomedical informatics May 20, 2022
The multi-modal and unstructured nature of observational data in Electronic Health Records (EHR) is currently a significant obstacle for the application of machine learning towards risk stratification. In this study, we develop a deep learning framew...
Early Detection of Cancer Pancreatic Neoplasms Deep Learning Time Factors Humans Electronic Health Records
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Recognition of Unknown Entities in Specific Financial Field Based on ERNIE-Doc-BiLSTM-CRF.

Computational intelligence and neuroscience May 14, 2022
The Internet is rich in information related to the financial field. The financial entity information text containing new internet vocabulary has a certain impact on the results of existing recognition algorithms. How to solve the problems of new voca...
Natural Language Processing Data Collection Algorithms Electronic Health Records Language
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Automated medical chart review for breast cancer outcomes research: a novel natural language processing extraction system.

BMC medical research methodology May 12, 2022
BACKGROUND: Manually extracted data points from health records are collated on an institutional, provincial, and national level to facilitate clinical research. However, the labour-intensive clinical chart review process puts an increasing burden on ...
Female Breast Neoplasms Humans Electronic Health Records Information Storage and Retrieval Outcome Assessment, Health Care Natural Language Processing Research Report
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SemClinBr - a multi-institutional and multi-specialty semantically annotated corpus for Portuguese clinical NLP tasks.

Journal of biomedical semantics May 8, 2022
BACKGROUND: The high volume of research focusing on extracting patient information from electronic health records (EHRs) has led to an increase in the demand for annotated corpora, which are a precious resource for both the development and evaluation...
Portugal Humans Medicine Reproducibility of Results Electronic Health Records Natural Language Processing
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