Natural Language Processing
"Natural Language Processing" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
Computer processing of a language with rules that reflect and describe current usage rather than prescribed usage.
| Descriptor ID |
D009323
|
| MeSH Number(s) |
L01.224.050.375.580
|
| Concept/Terms |
Natural Language Processing- Natural Language Processing
- Language Processing, Natural
- Language Processings, Natural
- Natural Language Processings
- Processing, Natural Language
- Processings, Natural Language
|
Below are MeSH descriptors whose meaning is more general than "Natural Language Processing".
Below are MeSH descriptors whose meaning is more specific than "Natural Language Processing".
This graph shows the total number of publications written about "Natural Language Processing" by people in this website by year, and whether "Natural Language Processing" was a major or minor topic of these publications.
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| Year | Major Topic | Minor Topic | Total |
|---|
| 2003 | 1 | 0 | 1 |
| 2012 | 1 | 0 | 1 |
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Below are the most recent publications written about "Natural Language Processing" by people in Profiles.
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Improving Neurology Clinical Care With Natural Language Processing Tools. Neurology. 2023 Nov 27; 101(22):1010-1018.
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External validation of a machine learning classifier to identify unhealthy alcohol use in hospitalized patients. Addiction. 2022 Apr; 117(4):925-933.
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Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups. J Am Med Inform Assoc. 2021 10 12; 28(11):2393-2403.
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Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients. BMC Med Inform Decis Mak. 2020 04 29; 20(1):79.
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Validation of an alcohol misuse classifier in hospitalized patients. Alcohol. 2020 05; 84:49-55.
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Subtypes in patients with opioid misuse: A prognostic enrichment strategy using electronic health record data in hospitalized patients. PLoS One. 2019; 14(7):e0219717.
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Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation. J Am Med Inform Assoc. 2019 03 01; 26(3):254-261.
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Applying a natural language processing tool to electronic health records to assess performance on colonoscopy quality measures. Gastrointest Endosc. 2012 Jun; 75(6):1233-9.e14.
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Electronic interpretation of chest radiograph reports to detect central venous catheters. Infect Control Hosp Epidemiol. 2003 Dec; 24(12):950-4.