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

Year Number of Results
1954 1
1957 1
1962 1
1965 2
1970 1
1971 1
1972 3
1974 2
1975 5
1976 3
1977 2
1978 2
1979 4
1980 8
1981 3
1982 6
1983 8
1984 5
1985 5
1986 5
1987 8
1988 4
1989 11
1990 14
1991 12
1992 12
1993 20
1994 12
1995 21
1996 27
1997 23
1998 24
1999 31
2000 47
2001 44
2002 51
2003 47
2004 57
2005 63
2006 85
2007 99
2008 105
2009 106
2010 107
2011 118
2012 146
2013 207
2014 265
2015 384
2016 643
2017 1352
2018 3084
2019 5608
2020 9317
2021 14477
2022 19621
2023 21305
2024 4529

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74,097 results

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Page 1
Deep-learning seismology.
Mousavi SM, Beroza GC. Mousavi SM, et al. Science. 2022 Aug 12;377(6607):eabm4470. doi: 10.1126/science.abm4470. Epub 2022 Aug 12. Science. 2022. PMID: 35951699 Review.
The availability of large-scale seismic datasets and the suitability of deep-learning techniques for seismic data processing have pushed deep learning to the forefront of fundamental, long-standing research investigations in seismology. ...Deep
The availability of large-scale seismic datasets and the suitability of deep-learning techniques for seismic data processing h …
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis.
van der Velden BHM, Kuijf HJ, Gilhuijs KGA, Viergever MA. van der Velden BHM, et al. Med Image Anal. 2022 Jul;79:102470. doi: 10.1016/j.media.2022.102470. Epub 2022 May 4. Med Image Anal. 2022. PMID: 35576821 Free article. Review.
With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes decision making areas such as medical image analysis. This survey presents an overview of explainable artificial intelligence (XAI) used in …
With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes …
Emerging role of deep learning-based artificial intelligence in tumor pathology.
Jiang Y, Yang M, Wang S, Li X, Sun Y. Jiang Y, et al. Cancer Commun (Lond). 2020 Apr;40(4):154-166. doi: 10.1002/cac2.12012. Epub 2020 Apr 11. Cancer Commun (Lond). 2020. PMID: 32277744 Free PMC article. Review.
The development of digital pathology and progression of state-of-the-art algorithms for computer vision have led to increasing interest in the use of artificial intelligence (AI), especially deep learning (DL)-based AI, in tumor pathology. The DL-based algorithms ha …
The development of digital pathology and progression of state-of-the-art algorithms for computer vision have led to increasing interest in t …
Deep learning for electroencephalogram (EEG) classification tasks: a review.
Craik A, He Y, Contreras-Vidal JL. Craik A, et al. J Neural Eng. 2019 Jun;16(3):031001. doi: 10.1088/1741-2552/ab0ab5. Epub 2019 Feb 26. J Neural Eng. 2019. PMID: 30808014 Review.
(2) What input formulations have been used for training the deep networks? (3) Are there specific deep learning network structures suitable for specific types of tasks? ...SIGNIFICANCE: This review summarizes the current practices and performance outcomes in …
(2) What input formulations have been used for training the deep networks? (3) Are there specific deep learning network …
Multimodal deep learning for biomedical data fusion: a review.
Stahlschmidt SR, Ulfenborg B, Synnergren J. Stahlschmidt SR, et al. Brief Bioinform. 2022 Mar 10;23(2):bbab569. doi: 10.1093/bib/bbab569. Brief Bioinform. 2022. PMID: 35089332 Free PMC article. Review.
Biomedical data are becoming increasingly multimodal and thereby capture the underlying complex relationships among biological processes. Deep learning (DL)-based data fusion strategies are a popular approach for modeling these nonlinear relationships. ...Finally, w …
Biomedical data are becoming increasingly multimodal and thereby capture the underlying complex relationships among biological processes. …
Deep learning in clinical natural language processing: a methodical review.
Wu S, Roberts K, Datta S, Du J, Ji Z, Si Y, Soni S, Wang Q, Wei Q, Xiang Y, Zhao B, Xu H. Wu S, et al. J Am Med Inform Assoc. 2020 Mar 1;27(3):457-470. doi: 10.1093/jamia/ocz200. J Am Med Inform Assoc. 2020. PMID: 31794016 Free PMC article. Review.
OBJECTIVE: This article methodically reviews the literature on deep learning (DL) for natural language processing (NLP) in the clinical domain, providing quantitative analysis to answer 3 research questions concerning methods, scope, and context of current research. …
OBJECTIVE: This article methodically reviews the literature on deep learning (DL) for natural language processing (NLP) in the …
Deep Learning in Diverse Intelligent Sensor Based Systems.
Zhu Y, Wang M, Yin X, Zhang J, Meijering E, Hu J. Zhu Y, et al. Sensors (Basel). 2022 Dec 21;23(1):62. doi: 10.3390/s23010062. Sensors (Basel). 2022. PMID: 36616657 Free PMC article. Review.
Deep learning has become a predominant method for solving data analysis problems in virtually all fields of science and engineering. ...It also provides a comprehensive summary of deep learning implementation tips and links to tutorials, open-source co
Deep learning has become a predominant method for solving data analysis problems in virtually all fields of science and engine
Deep Learning in Medical Hyperspectral Images: A Review.
Cui R, Yu H, Xu T, Xing X, Cao X, Yan K, Chen J. Cui R, et al. Sensors (Basel). 2022 Dec 13;22(24):9790. doi: 10.3390/s22249790. Sensors (Basel). 2022. PMID: 36560157 Free PMC article. Review.
With the continuous progress of development, deep learning has made good progress in the analysis and recognition of images, which has also triggered some researchers to explore the area of combining deep learning with hyperspectral medical images and …
With the continuous progress of development, deep learning has made good progress in the analysis and recognition of images, w …
Deep learning a boon for biophotonics?
Pradhan P, Guo S, Ryabchykov O, Popp J, Bocklitz TW. Pradhan P, et al. J Biophotonics. 2020 Jun;13(6):e201960186. doi: 10.1002/jbio.201960186. Epub 2020 Mar 30. J Biophotonics. 2020. PMID: 32167235 Review.
This review covers original articles using deep learning in the biophotonic field published in the last years. ...We conclude this review by addressing the potential applications and challenges of using deep learning for biophotonic data....
This review covers original articles using deep learning in the biophotonic field published in the last years. ...We conclude …
Protein design via deep learning.
Ding W, Nakai K, Gong H. Ding W, et al. Brief Bioinform. 2022 May 13;23(3):bbac102. doi: 10.1093/bib/bbac102. Brief Bioinform. 2022. PMID: 35348602 Free PMC article. Review.
In this review, we retrospect the major aspects of current advances in deep-learning-based design procedures and illustrate their novelty in comparison with conventional knowledge-based approaches through noticeable cases. We not only describe deep learnin
In this review, we retrospect the major aspects of current advances in deep-learning-based design procedures and illustrate th …
74,097 results
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