Pattern Recognition, Automated
"Pattern Recognition, Automated" 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.
In INFORMATION RETRIEVAL, machine-sensing or identification of visible patterns (shapes, forms, and configurations). (Harrod's Librarians' Glossary, 7th ed)
| Descriptor ID |
D010363
|
| MeSH Number(s) |
L01.399.750
|
| Concept/Terms |
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Below are MeSH descriptors whose meaning is more general than "Pattern Recognition, Automated".
Below are MeSH descriptors whose meaning is more specific than "Pattern Recognition, Automated".
This graph shows the total number of publications written about "Pattern Recognition, Automated" by people in this website by year, and whether "Pattern Recognition, Automated" 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 |
|---|
| 1998 | 1 | 0 | 1 |
| 2000 | 1 | 0 | 1 |
| 2001 | 0 | 1 | 1 |
| 2002 | 1 | 2 | 3 |
| 2003 | 1 | 2 | 3 |
| 2004 | 3 | 1 | 4 |
| 2005 | 1 | 2 | 3 |
| 2006 | 4 | 2 | 6 |
| 2007 | 2 | 4 | 6 |
| 2008 | 4 | 0 | 4 |
| 2009 | 3 | 2 | 5 |
| 2010 | 6 | 2 | 8 |
| 2011 | 3 | 1 | 4 |
| 2012 | 4 | 4 | 8 |
| 2013 | 3 | 0 | 3 |
| 2014 | 1 | 3 | 4 |
| 2015 | 0 | 2 | 2 |
| 2016 | 0 | 1 | 1 |
| 2017 | 1 | 1 | 2 |
| 2018 | 2 | 2 | 4 |
| 2019 | 0 | 2 | 2 |
| 2020 | 1 | 1 | 2 |
| 2021 | 0 | 2 | 2 |
| 2022 | 1 | 0 | 1 |
| 2023 | 1 | 0 | 1 |
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click here.
Below are the most recent publications written about "Pattern Recognition, Automated" by people in Profiles.
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Anandakrishnan M, Ross KE, Chen C, Shanker V, Cowart J, Wu CH. KSFinder-a knowledge graph model for link prediction of novel phosphorylated substrates of kinases. PeerJ. 2023; 11:e16164.
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Gavali S, Ross K, Chen C, Cowart J, Wu CH. A knowledge graph representation learning approach to predict novel kinase-substrate interactions. Mol Omics. 2022 10 31; 18(9):853-864.
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Chen C, Ross KE, Gavali S, Cowart JE, Wu CH. COVID-19 Knowledge Graph from semantic integration of biomedical literature and databases. Bioinformatics. 2021 12 07; 37(23):4597-4598.
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Moore C, Valenti A, Robinson E, Perkins R. Using Log Data to Measure Provider EHR Activity at a Cancer Center during Rapid Telemedicine Deployment. Appl Clin Inform. 2021 05; 12(3):629-636.
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Bouteldja N, Klinkhammer BM, B?low RD, Droste P, Otten SW, Freifrau von Stillfried S, Moellmann J, Sheehan SM, Korstanje R, Menzel S, Bankhead P, Mietsch M, Drummer C, Lehrke M, Kramann R, Floege J, Boor P, Merhof D. Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology. J Am Soc Nephrol. 2021 01; 32(1):52-68.
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Ratnagiri MV, Ryan L, Strang A, Heinle R, Rahman T, Shaffer TH. Machine learning for automatic identification of thoracoabdominal asynchrony in children. Pediatr Res. 2021 04; 89(5):1232-1238.
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Chitalia RD, Rowland J, McDonald ES, Pantalone L, Cohen EA, Gastounioti A, Feldman M, Schnall M, Conant E, Kontos D. Imaging Phenotypes of Breast Cancer Heterogeneity in Preoperative Breast Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) Scans Predict 10-Year Recurrence. Clin Cancer Res. 2020 02 15; 26(4):862-869.
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Bahrami N, Retson T, Blansit K, Wang K, Hsiao A. Automated selection of myocardial inversion time with a convolutional neural network: Spatial temporal ensemble myocardium inversion network (STEMI-NET). Magn Reson Med. 2019 05; 81(5):3283-3291.
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Lee AJ, Chang I, Burel JG, Lindestam Arlehamn CS, Mandava A, Weiskopf D, Peters B, Sette A, Scheuermann RH, Qian Y. DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data. Cytometry A. 2018 06; 93(6):597-610.
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Li P, Jiang X, Kambhamettu C, Shatkay H. Compound image segmentation of published biomedical figures. Bioinformatics. 2018 04 01; 34(7):1192-1199.