 Machine Learning
"Machine Learning" 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.
A type of ARTIFICIAL INTELLIGENCE that enable COMPUTERS to independently initiate and execute LEARNING when exposed to new data.
| Descriptor ID |
D000069550
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| MeSH Number(s) |
G17.035.250.500 L01.224.050.375.530
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| Concept/Terms |
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Below are MeSH descriptors whose meaning is more general than "Machine Learning".
Below are MeSH descriptors whose meaning is more specific than "Machine Learning".
This graph shows the total number of publications written about "Machine Learning" by people in this website by year, and whether "Machine Learning" 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 |
|---|
| 2015 | 3 | 5 | 8 | | 2016 | 0 | 3 | 3 | | 2017 | 9 | 8 | 17 | | 2018 | 7 | 3 | 10 | | 2019 | 12 | 9 | 21 | | 2020 | 15 | 9 | 24 | | 2021 | 8 | 16 | 24 | | 2022 | 5 | 4 | 9 |
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Below are the most recent publications written about "Machine Learning" by people in Profiles.
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Suresh K, Severn C, Ghosh D. Survival prediction models: an introduction to discrete-time modeling. BMC Med Res Methodol. 2022 07 26; 22(1):207.
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Severn C, Suresh K, Görg C, Choi YS, Jain R, Ghosh D. A Pipeline for the Implementation and Visualization of Explainable Machine Learning for Medical Imaging Using Radiomics Features. Sensors (Basel). 2022 Jul 12; 22(14).
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Starr AJ, Julka M, Nethi A, Watkins JD, Fairchild RW, Rinehart D, Park C, Dumas RP, Box HN, Cripps MW. Parkland Trauma Index of Mortality: Real-Time Predictive Model for Trauma Patients. J Orthop Trauma. 2022 06 01; 36(6):280-286.
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Pfaff ER, Girvin AT, Bennett TD, Bhatia A, Brooks IM, Deer RR, Dekermanjian JP, Jolley SE, Kahn MG, Kostka K, McMurry JA, Moffitt R, Walden A, Chute CG, Haendel MA. Identifying who has long COVID in the USA: a machine learning approach using N3C data. Lancet Digit Health. 2022 07; 4(7):e532-e541.
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McKearney RM, Bell SL, Chesnaye MA, Simpson DM. Auditory Brainstem Response Detection Using Machine Learning: A Comparison With Statistical Detection Methods. Ear Hear. 2022 May/Jun; 43(3):949-960.
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Porras AR, Rosenbaum K, Tor-Diez C, Summar M, Linguraru MG. A machine learning-based screening tool for genetic syndromes in children - Authors' reply. Lancet Digit Health. 2022 05; 4(5):e296.
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Edward JA, Josey K, Bahn G, Caplan L, Reusch JEB, Reaven P, Ghosh D, Raghavan S. Heterogeneous treatment effects of intensive glycemic control on major adverse cardiovascular events in the ACCORD and VADT trials: a machine-learning analysis. Cardiovasc Diabetol. 2022 04 27; 21(1):58.
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Gartstein MA, Seamon DE, Mattera JA, Bosquet Enlow M, Wright RJ, Perez-Edgar K, Buss KA, LoBue V, Bell MA, Goodman SH, Spieker S, Bridgett DJ, Salisbury AL, Gunnar MR, Mliner SB, Muzik M, Stifter CA, Planalp EM, Mehr SA, Spelke ES, Lukowski AF, Groh AM, Lickenbrock DM, Santelli R, Du Rocher Schudlich T, Anzman-Frasca S, Thrasher C, Diaz A, Dayton C, Moding KJ, Jordan EM. Using machine learning to understand age and gender classification based on infant temperament. PLoS One. 2022; 17(4):e0266026.
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Cox M, Reid N, Panagides JC, Di Capua J, DeCarlo C, Dua A, Kalva S, Kalpathy-Cramer J, Daye D. Interpretable Machine Learning for the Prediction of Amputation Risk Following Lower Extremity Infrainguinal Endovascular Interventions for Peripheral Arterial Disease. Cardiovasc Intervent Radiol. 2022 May; 45(5):633-640.
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Voros J, Rise R, Sherman S, Durell A, Anderson AP, Clark TK. A machine learning approach to identify stochastic resonance in human perceptual thresholds. J Neurosci Methods. 2022 05 15; 374:109559.
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