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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1957 1
1962 1
1964 4
1965 1
1966 2
1967 1
1968 2
1969 2
1970 1
1972 1
1973 1
1974 2
1975 3
1976 3
1978 3
1979 1
1980 3
1981 1
1982 3
1983 3
1984 3
1985 4
1986 6
1987 3
1988 7
1989 7
1990 7
1991 12
1992 15
1993 22
1994 24
1995 32
1996 30
1997 33
1998 30
1999 34
2000 57
2001 81
2002 97
2003 120
2004 183
2005 247
2006 322
2007 409
2008 499
2009 595
2010 713
2011 1139
2012 1487
2013 1923
2014 2418
2015 3286
2016 3915
2017 5278
2018 8324
2019 12637
2020 18124
2021 25420
2022 14922
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91,458 results
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Machine Learning in Medicine.
Deo RC. Deo RC. Circulation. 2015 Nov 17;132(20):1920-30. doi: 10.1161/CIRCULATIONAHA.115.001593. Circulation. 2015. PMID: 26572668 Free PMC article. Review.
The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical da …
The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from …
Machine Learning and Deep Learning in Medical Imaging: Intelligent Imaging.
Currie G, Hawk KE, Rohren E, Vial A, Klein R. Currie G, et al. J Med Imaging Radiat Sci. 2019 Dec;50(4):477-487. doi: 10.1016/j.jmir.2019.09.005. Epub 2019 Oct 7. J Med Imaging Radiat Sci. 2019. PMID: 31601480 Review.
An understanding of the principles and application of radiomics, artificial neural networks, machine learning, and deep learning is an essential foundation to weave design solutions that accommodate ethical and regulatory requirements, and to craft AI-based a …
An understanding of the principles and application of radiomics, artificial neural networks, machine learning, and deep lea …
Machine Learning Methods in Drug Discovery.
Patel L, Shukla T, Huang X, Ussery DW, Wang S. Patel L, et al. Molecules. 2020 Nov 12;25(22):5277. doi: 10.3390/molecules25225277. Molecules. 2020. PMID: 33198233 Free PMC article. Review.
The methods for designing drug targets and novel drug discovery now routinely combine machine learning and deep learning algorithms to enhance the efficiency, efficacy, and quality of developed outputs. ...In this review, machine learning and de …
The methods for designing drug targets and novel drug discovery now routinely combine machine learning and deep learning …
Artificial intelligence to deep learning: machine intelligence approach for drug discovery.
Gupta R, Srivastava D, Sahu M, Tiwari S, Ambasta RK, Kumar P. Gupta R, et al. Mol Divers. 2021 Aug;25(3):1315-1360. doi: 10.1007/s11030-021-10217-3. Epub 2021 Apr 12. Mol Divers. 2021. PMID: 33844136 Free PMC article. Review.
Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of …
Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning compris …
eDoctor: machine learning and the future of medicine.
Handelman GS, Kok HK, Chandra RV, Razavi AH, Lee MJ, Asadi H. Handelman GS, et al. J Intern Med. 2018 Dec;284(6):603-619. doi: 10.1111/joim.12822. Epub 2018 Sep 3. J Intern Med. 2018. PMID: 30102808 Free article. Review.
Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. ...
Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statist …
A guide to machine learning for biologists.
Greener JG, Kandathil SM, Moffat L, Jones DT. Greener JG, et al. Nat Rev Mol Cell Biol. 2022 Jan;23(1):40-55. doi: 10.1038/s41580-021-00407-0. Epub 2021 Sep 13. Nat Rev Mol Cell Biol. 2022. PMID: 34518686 Review.
All machine learning techniques fit models to data; however, the specific methods are quite varied and can at first glance seem bewildering. ...We describe how different techniques may be suited to specific types of biological data, and also discuss some best practi …
All machine learning techniques fit models to data; however, the specific methods are quite varied and can at first glance see …
Machine learning for clinical decision support in infectious diseases: a narrative review of current applications.
Peiffer-Smadja N, Rawson TM, Ahmad R, Buchard A, Georgiou P, Lescure FX, Birgand G, Holmes AH. Peiffer-Smadja N, et al. Clin Microbiol Infect. 2020 May;26(5):584-595. doi: 10.1016/j.cmi.2019.09.009. Epub 2019 Sep 17. Clin Microbiol Infect. 2020. PMID: 31539636 Free article. Review.
BACKGROUND: Machine learning (ML) is a growing field in medicine. This narrative review describes the current body of literature on ML for clinical decision support in infectious diseases (ID). ...
BACKGROUND: Machine learning (ML) is a growing field in medicine. This narrative review describes the current body of literatu …
Introduction to Machine Learning, Neural Networks, and Deep Learning.
Choi RY, Coyner AS, Kalpathy-Cramer J, Chiang MF, Campbell JP. Choi RY, et al. Transl Vis Sci Technol. 2020 Feb 27;9(2):14. doi: 10.1167/tvst.9.2.14. Transl Vis Sci Technol. 2020. PMID: 32704420 Free PMC article.
PURPOSE: To present an overview of current machine learning methods and their use in medical research, focusing on select machine learning techniques, best practices, and deep learning. METHODS: A systematic literature search in PubMed was perfo …
PURPOSE: To present an overview of current machine learning methods and their use in medical research, focusing on select m …
Machine learning and applications in microbiology.
Goodswen SJ, Barratt JLN, Kennedy PJ, Kaufer A, Calarco L, Ellis JT. Goodswen SJ, et al. FEMS Microbiol Rev. 2021 Sep 8;45(5):fuab015. doi: 10.1093/femsre/fuab015. FEMS Microbiol Rev. 2021. PMID: 33724378 Free PMC article. Review.
The aim of this review is to identify key points required to start the journey of becoming an effective machine learning practitioner. These key points are further reinforced with an evaluation of how machine learning has been applied so far in a broad …
The aim of this review is to identify key points required to start the journey of becoming an effective machine learning pract …
Machine Learning Principles for Radiology Investigators.
Borstelmann SM. Borstelmann SM. Acad Radiol. 2020 Jan;27(1):13-25. doi: 10.1016/j.acra.2019.07.030. Acad Radiol. 2020. PMID: 31818379 Review.
However, the field of machine learning encompasses multiple statistics-based techniques useful for investigators, which may be complementary to deep learning approaches. After a refresher in basic statistical concepts, relevant considerations for machine …
However, the field of machine learning encompasses multiple statistics-based techniques useful for investigators, which may be …
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