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.

MeSH information

Definition | Details | More General Concepts | Related Concepts | More Specific Concepts

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".

Information Science [L]
Information Science [L01]
Computing Methodologies [L01.224]
Algorithms [L01.224.050]
Artificial Intelligence [L01.224.050.375]
Natural Language Processing [L01.224.050.375.580]

Below are MeSH descriptors whose meaning is related to "Natural Language Processing".

Below are MeSH descriptors whose meaning is more specific than "Natural Language Processing".

publications

Timeline | Most Recent

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.

Bar chart showing 27 publications over 14 distinct years, with a maximum of 6 publications in 2024

To see the data from this visualization as text, click here.

Year	Major Topic	Minor Topic	Total
2002	1	0	1
2006	3	0	3
2007	2	1	3
2009	1	0	1
2012	2	0	2
2013	1	0	1
2014	2	1	3
2015	1	1	2
2016	0	1	1
2017	1	0	1
2018	1	0	1
2019	1	0	1
2022	1	0	1
2024	5	1	6

Below are the most recent publications written about "Natural Language Processing" by people in Profiles.

Tabaie A, Tran A, Calabria T, Bennett SS, Milicia A, Weintraub W, Gallagher WJ, Yosaitis J, Schubel LC, Hill MA, Smith KM, Miller K. Evaluation of a Natural Language Processing Approach to Identify Diagnostic Errors and Analysis of Safety Learning System Case Review Data: Retrospective Cohort Study. J Med Internet Res. 2024 08 26; 26:e50935.

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Fares MY, Liu HH, da Silva Etges APB, Zhang B, Warner JJP, Olson JJ, Fedorka CJ, Khan AZ, Best MJ, Kirsch JM, Simon JE, Sanders B, Costouros JG, Zhang X, Jones P, Haas DA, Abboud JA. Utility of Machine Learning, Natural Language Processing, and Artificial Intelligence in Predicting Hospital Readmissions After Orthopaedic Surgery: A Systematic Review and Meta-Analysis. JBJS Rev. 2024 Aug 01; 12(8).

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Vasan V, Cheng CP, Edalati S, Mandloi S, Lerner DK, Del Signore A, Schaberg M, Govindaraj S, Rabinowitz M, Nyquist G, Iloreta AM. Gender-based linguistic differences in letters of recommendation for rhinology fellowship over time: A dual-institutional follow-up study using natural language processing and deep learning. Int Forum Allergy Rhinol. 2024 Nov; 14(11):1814-1817.

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Yao JJ, Aggarwal M, Lopez RD, Namdari S. Large Language Models in Orthopaedics: Definitions, Uses, and Limitations. J Bone Joint Surg Am. 2024 Aug 07; 106(15):1411-1418.

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Mertes PM, Morgand C, Barach P, Jurkolow G, Assmann KE, Dufetelle E, Susplugas V, Alauddin B, Yavordios PG, Tourres J, Dumeix JM, Capdevila X. Validation of a natural language processing algorithm using national reporting data to improve identification of anesthesia-related ADVerse evENTs: The "ADVENTURE" study. Anaesth Crit Care Pain Med. 2024 Aug; 43(4):101390.

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Parasa S, Berzin T, Leggett C, Gross S, Repici A, Ahmad OF, Chiang A, Coelho-Prabhu N, Cohen J, Dekker E, Keswani RN, Kahn CE, Hassan C, Petrick N, Mountney P, Ng J, Riegler M, Mori Y, Saito Y, Thakkar S, Waxman I, Wallace MB, Sharma P. Consensus statements on the current landscape of artificial intelligence applications in endoscopy, addressing roadblocks, and advancing artificial intelligence in gastroenterology. Gastrointest Endosc. 2025 Jan; 101(1):2-9.e1.

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Boitano LT, DeVivo G, Robichaud DI, Okuhn S, Steppacher RC, Simons JP, Aiello FA, Jones D, Judelson D, Nguyen T, Sorensen C, Schanzer A. Successful implementation of a nurse-navigator-run program using natural language processing identifying patients with an abdominal aortic aneurysm. J Vasc Surg. 2023 Mar; 77(3):922-929.

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Su P, Li G, Wu C, Vijay-Shanker K. Using distant supervision to augment manually annotated data for relation extraction. PLoS One. 2019; 14(7):e0216913.

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Ding R, Qu Y, Wu CH, Vijay-Shanker K. Automatic gene annotation using GO terms from cellular component domain. BMC Med Inform Decis Mak. 2018 12 07; 18(Suppl 5):119.

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Mahmood ASMA, Rao S, McGarvey P, Wu C, Madhavan S, Vijay-Shanker K. eGARD: Extracting associations between genomic anomalies and drug responses from text. PLoS One. 2017; 12(12):e0189663.

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