 Artificial Intelligence
"Artificial Intelligence" 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.
The study and implementation of techniques and methods for designing computer systems to perform functions normally associated with human intelligence, such as understanding language, learning, reasoning, problem solving, etc.
| Descriptor ID |
D001185
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| MeSH Number(s) |
L01.224.065
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| Concept/Terms |
Artificial Intelligence- Artificial Intelligence
- Intelligence, Artificial
- Computer Reasoning
- Reasoning, Computer
- Machine Intelligence
- Intelligence, Machine
- AI (Artificial Intelligence)
- AIs (Artificial Intelligence)
Knowledge Representation (Computer)- Knowledge Representation (Computer)
- Knowledge Representations (Computer)
- Representation, Knowledge (Computer)
- Representations, Knowledge (Computer)
Computer Vision Systems- Computer Vision Systems
- Computer Vision System
- System, Computer Vision
- Systems, Computer Vision
- Vision System, Computer
- Vision Systems, Computer
Knowledge Acquisition (Computer)- Knowledge Acquisition (Computer)
- Acquisition, Knowledge (Computer)
- Acquisitions, Knowledge (Computer)
- Knowledge Acquisitions (Computer)
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Below are MeSH descriptors whose meaning is more general than "Artificial Intelligence".
Below are MeSH descriptors whose meaning is more specific than "Artificial Intelligence".
This graph shows the total number of publications written about "Artificial Intelligence" by people in this website by year, and whether "Artificial Intelligence" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 1987 | 1 | 0 | 1 | | 1994 | 4 | 0 | 4 | | 1995 | 0 | 1 | 1 | | 1996 | 0 | 1 | 1 | | 1998 | 1 | 0 | 1 | | 2000 | 1 | 2 | 3 | | 2001 | 1 | 1 | 2 | | 2002 | 5 | 2 | 7 | | 2003 | 1 | 3 | 4 | | 2004 | 4 | 5 | 9 | | 2005 | 8 | 6 | 14 | | 2006 | 6 | 4 | 10 | | 2007 | 4 | 3 | 7 | | 2008 | 2 | 7 | 9 | | 2009 | 5 | 5 | 10 | | 2010 | 3 | 4 | 7 | | 2011 | 3 | 1 | 4 | | 2012 | 1 | 2 | 3 | | 2013 | 2 | 1 | 3 | | 2014 | 1 | 3 | 4 | | 2018 | 2 | 0 | 2 | | 2019 | 3 | 3 | 6 | | 2020 | 12 | 3 | 15 | | 2021 | 9 | 8 | 17 | | 2022 | 5 | 5 | 10 |
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Below are the most recent publications written about "Artificial Intelligence" by people in Profiles.
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Onishchenko D, Rubin DS, van Horne JR, Ward RP, Chattopadhyay I. Cardiac Comorbidity Risk Score: Zero-Burden Machine Learning to Improve Prediction of Postoperative Major Adverse Cardiac Events in Hip and Knee Arthroplasty. J Am Heart Assoc. 2022 Aug 02; 11(15):e023745.
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Mourad R, Kolisnyk S, Baiun Y, Falk A, Yuriy T, Valerii F, Kopeev A, Suldina O, Pospelov A, Kim J, Rusakov A, Lebl DR. Performance of hybrid artificial intelligence in determining candidacy for lumbar stenosis surgery. Eur Spine J. 2022 Aug; 31(8):2149-2155.
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Ojha V, Khalique OK, Khurana R, Lorenzatti D, Leung SW, Lawton B, Slesnick TC, Cavalcante JC, Ducci CB, Patel AR, Prieto CC, Plein S, Raman SV, Salerno M, Parwani P. Highlights of the Virtual Society for Cardiovascular Magnetic Resonance 2022 Scientific Conference: CMR: improving cardiovascular care around the world. J Cardiovasc Magn Reson. 2022 06 20; 24(1):38.
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Makhni S, Chin MH, Fahrenbach J, Rojas JC. Equity Challenges for Artificial Intelligence Algorithms in Health Care. Chest. 2022 05; 161(5):1343-1346.
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Wang S, Chauhan D, Patel H, Amir-Khalili A, da Silva IF, Sojoudi A, Friedrich S, Singh A, Landeras L, Miller T, Ameyaw K, Narang A, Kawaji K, Tang Q, Mor-Avi V, Patel AR. Assessment of right ventricular size and function from cardiovascular magnetic resonance images using artificial intelligence. J Cardiovasc Magn Reson. 2022 04 11; 24(1):27.
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Pun FW, Leung GHD, Leung HW, Liu BHM, Long X, Ozerov IV, Wang J, Ren F, Aliper A, Izumchenko E, Moskalev A, de Magalhães JP, Zhavoronkov A. Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine. Aging (Albany NY). 2022 03 29; 14(6):2475-2506.
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Ha AY, Do BH, Bartret AL, Fang CX, Hsiao A, Lutz AM, Banerjee I, Riley GM, Rubin DL, Stevens KJ, Wang E, Wang S, Beaulieu CF, Hurt B. Automating Scoliosis Measurements in Radiographic Studies with Machine Learning: Comparing Artificial Intelligence and Clinical Reports. J Digit Imaging. 2022 Jun; 35(3):524-533.
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Brunt EM, Clouston AD, Goodman Z, Guy C, Kleiner DE, Lackner C, Tiniakos DG, Wee A, Yeh M, Leow WQ, Chng E, Ren Y, Boon Bee GG, Powell EE, Rinella M, Sanyal AJ, Neuschwander-Tetri B, Younossi Z, Charlton M, Ratziu V, Harrison SA, Tai D, Anstee QM. Complexity of ballooned hepatocyte feature recognition: Defining a training atlas for artificial intelligence-based imaging in NAFLD. J Hepatol. 2022 05; 76(5):1030-1041.
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Treviño M, Birdsong G, Carrigan A, Choyke P, Drew T, Eckstein M, Fernandez A, Gallas BD, Giger M, Hewitt SM, Horowitz TS, Jiang YV, Kudrick B, Martinez-Conde S, Mitroff S, Nebeling L, Saltz J, Samuelson F, Seltzer SE, Shabestari B, Shankar L, Siegel E, Tilkin M, Trueblood JS, Van Dyke AL, Venkatesan AM, Whitney D, Wolfe JM. Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration. JNCI Cancer Spectr. 2022 01 05; 6(1).
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Drogan C, Kupfer SS. Colorectal Cancer Screening Recommendations and Outcomes in Lynch Syndrome. Gastrointest Endosc Clin N Am. 2022 Jan; 32(1):59-74.
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