 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, and problem solving.
| 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
- Computational Intelligence
- Computational Intelligences
- Intelligence, Computational
- Intelligences, Computational
- Machine Intelligence
- Intelligence, Machine
- AI (Artificial Intelligence)
- AIs (Artificial Intelligence)
- Computer Reasoning
- Reasoning, Computer
Knowledge Acquisition (Computer)- Knowledge Acquisition (Computer)
- Acquisition, Knowledge (Computer)
- Acquisitions, Knowledge (Computer)
- Knowledge Acquisitions (Computer)
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
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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 UAMS Profiles 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 |
|---|
| 2022 | 2 | 2 | 4 | | 2021 | 6 | 2 | 8 | | 2020 | 3 | 0 | 3 | | 2019 | 2 | 0 | 2 | | 2013 | 0 | 3 | 3 | | 2011 | 0 | 1 | 1 | | 2010 | 0 | 2 | 2 | | 2009 | 2 | 1 | 3 | | 2008 | 8 | 6 | 14 | | 2007 | 2 | 3 | 5 | | 2006 | 0 | 1 | 1 | | 2005 | 2 | 0 | 2 | | 2002 | 1 | 0 | 1 | | 1995 | 0 | 1 | 1 |
To return to the timeline, click here.
Below are the most recent publications written about "Artificial Intelligence" by people in Profiles over the past ten years.
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Seker E, Talburt JR, Greer ML. Preprocessing to Address Bias in Healthcare Data. Stud Health Technol Inform. 2022 May 25; 294:327-331.
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Duarte-Rojo A, Sejdic E. Artificial Intelligence and the Risk for Intuition Decline in Clinical Medicine. Am J Gastroenterol. 2022 03 01; 117(3):401-402.
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Al-Aswad LA, Ramachandran R, Schuman JS, Medeiros F, Eydelman MB. Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression. Ophthalmol Glaucoma. 2022 Sep-Oct; 5(5):e16-e25.
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Yang F, Darsey JA, Ghosh A, Li HY, Yang MQ, Wang S. Artificial Intelligence and Cancer Drug Development. Recent Pat Anticancer Drug Discov. 2022; 17(1):2-8.
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Schuman JS, De Los Angeles Ramos Cadena M, McGee R, Al-Aswad LA, Medeiros FA. A Case for the Use of Artificial Intelligence in Glaucoma Assessment. Ophthalmol Glaucoma. 2022 May-Jun; 5(3):e3-e13.
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Khorsandi SE, Hardgrave HJ, Osborn T, Klutts G, Nigh J, Spencer-Cole RT, Kakos CD, Anastasiou I, Mavros MN, Giorgakis E. Artificial Intelligence in Liver Transplantation. Transplant Proc. 2021 Dec; 53(10):2939-2944.
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Blobel B, Ruotsalainen P, Brochhausen M. Autonomous Systems and Artificial Intelligence - Hype or Prerequisite for P5 Medicine? Stud Health Technol Inform. 2021 Oct 27; 285:3-14.
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Anastasiou J, Coronel E, Cazacu I, Saftoiu A, Berzin T. Artificial Intelligence-Assisted Diagnostic Approaches for Pancreatic Disease. Pancreas. 2021 09 01; 50(8):e69-e70.
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Guo Y, Zhang Y, Lyu T, Prosperi M, Wang F, Xu H, Bian J. The application of artificial intelligence and data integration in COVID-19 studies: a scoping review. J Am Med Inform Assoc. 2021 08 13; 28(9):2050-2067.
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Syed M, Syed S, Sexton K, Greer ML, Zozus M, Bhattacharyya S, Syed F, Prior F. Deep Learning Methods to Predict Mortality in COVID-19 Patients: A Rapid Scoping Review. Stud Health Technol Inform. 2021 May 27; 281:799-803.
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Sorensen JI, Nikam RM, Choudhary AK. Artificial intelligence in child abuse imaging. Pediatr Radiol. 2021 May; 51(6):1061-1064.
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Diaz O, Kushibar K, Osuala R, Linardos A, Garrucho L, Igual L, Radeva P, Prior F, Gkontra P, Lekadir K. Data preparation for artificial intelligence in medical imaging: A comprehensive guide to open-access platforms and tools. Phys Med. 2021 Mar; 83:25-37.
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Chen Z, Liu X, Hogan W, Shenkman E, Bian J. Applications of artificial intelligence in drug development using real-world data. Drug Discov Today. 2021 05; 26(5):1256-1264.
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Payrovnaziri SN, Chen Z, Rengifo-Moreno P, Miller T, Bian J, Chen JH, Liu X, He Z. Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review. J Am Med Inform Assoc. 2020 07 01; 27(7):1173-1185.
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Blobel B, Ruotsalainen P, Brochhausen M, Oemig F, Uribe GA. Autonomous Systems and Artificial Intelligence in Healthcare Transformation to 5P Medicine - Ethical Challenges. Stud Health Technol Inform. 2020 Jun 16; 270:1089-1093.
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Bona JP, Prior FW, Zozus MN, Brochhausen M. Enhancing Clinical Data and Clinical Research Data with Biomedical Ontologies - Insights from the Knowledge Representation Perspective. Yearb Med Inform. 2019 Aug; 28(1):140-151.
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Kromenacker B, Maarouf M, Shi VY. Augmented Intelligence in Dermatology: Fantasy or Future? Dermatology. 2019; 235(3):250-252.
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Nagarajan R, Scutari M. Impact of noise on molecular network inference. PLoS One. 2013; 8(12):e80735.
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Zhang C, Kodell RL. Subpopulation-specific confidence designation for more informative biomedical classification. Artif Intell Med. 2013 Jul; 58(3):155-63.
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