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1
A Survey of the Usages of Deep Learning for Natural Language Processing
A Survey of the Usages of Deep Learning for Natural Language Processing
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A Survey of the Usages of Deep Learning for Natural Language Processing

IEEE transaction on neural networks and learning systems, 2021-02, Vol.32 (2), p.604

EISSN: 2162-2388 ;DOI: 10.1109/TNNLS.2020.2979670 ;PMID: 32324570

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2
Can artificial intelligence help for scientific writing?
Can artificial intelligence help for scientific writing?
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Can artificial intelligence help for scientific writing?

Critical care (London, England), 2023-02, Vol.27 (1), p.75-75, Article 75 [Peer Reviewed Journal]

2023. The Author(s). ;COPYRIGHT 2023 BioMed Central Ltd. ;2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2023 ;ISSN: 1364-8535 ;EISSN: 1466-609X ;DOI: 10.1186/s13054-023-04380-2 ;PMID: 36841840

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3
Sentiment of Emojis
Sentiment of Emojis
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Sentiment of Emojis

PloS one, 2015-12, Vol.10 (12), p.e0144296-e0144296 [Peer Reviewed Journal]

COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Kralj Novak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2015 Kralj Novak et al 2015 Kralj Novak et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0144296 ;PMID: 26641093

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4
A comparative study of pretrained language models for long clinical text
A comparative study of pretrained language models for long clinical text
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A comparative study of pretrained language models for long clinical text

Journal of the American Medical Informatics Association : JAMIA, 2023-01, Vol.30 (2), p.340-347 [Peer Reviewed Journal]

The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com. ;The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com 2022 ;ISSN: 1067-5027 ;EISSN: 1527-974X ;DOI: 10.1093/jamia/ocac225 ;PMID: 36451266

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5
Personality, gender, and age in the language of social media: the open-vocabulary approach
Personality, gender, and age in the language of social media: the open-vocabulary approach
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Personality, gender, and age in the language of social media: the open-vocabulary approach

PloS one, 2013-09, Vol.8 (9), p.e73791-e73791 [Peer Reviewed Journal]

COPYRIGHT 2013 Public Library of Science ;2013 Schwartz et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2013 Schwartz et al 2013 Schwartz et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0073791 ;PMID: 24086296

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6
A call for deep-learning healthcare
A call for deep-learning healthcare
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A call for deep-learning healthcare

Nature medicine, 2019-01, Vol.25 (1), p.14-15 [Peer Reviewed Journal]

COPYRIGHT 2019 Nature Publishing Group ;Copyright Nature Publishing Group Jan 2019 ;ISSN: 1078-8956 ;EISSN: 1546-170X ;DOI: 10.1038/s41591-018-0320-3 ;PMID: 30617337

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7
SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach
SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach
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SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach

PloS one, 2019-05, Vol.14 (5), p.e0216456-e0216456 [Peer Reviewed Journal]

COPYRIGHT 2019 Public Library of Science ;COPYRIGHT 2019 Public Library of Science ;2019 Mousavi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2019 Mousavi et al 2019 Mousavi et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0216456 ;PMID: 31063501

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8
Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria
Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria
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Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria

The New England journal of medicine, 2021-07, Vol.385 (3), p.217-227 [Peer Reviewed Journal]

Copyright © 2021 Massachusetts Medical Society. All rights reserved. ;Copyright © 2021 Massachusetts Medical Society. ;COPYRIGHT 2021 Massachusetts Medical Society ;ISSN: 0028-4793 ;EISSN: 1533-4406 ;DOI: 10.1056/NEJMoa2027540 ;PMID: 34260835

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9
Scientists used ChatGPT to generate an entire paper from scratch - but is it any good?
Scientists used ChatGPT to generate an entire paper from scratch - but is it any good?
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Scientists used ChatGPT to generate an entire paper from scratch - but is it any good?

Nature (London), 2023-07, Vol.619 (7970), p.443 [Peer Reviewed Journal]

EISSN: 1476-4687 ;DOI: 10.1038/d41586-023-02218-z ;PMID: 37419951

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10
Ethical implications of conversational agents in global public health
Ethical implications of conversational agents in global public health
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Ethical implications of conversational agents in global public health

Bulletin of the World Health Organization, 2020-04, Vol.98 (4), p.285-287 [Peer Reviewed Journal]

COPYRIGHT 2020 World Health Organization ;COPYRIGHT 2020 World Health Organization ;Copyright World Health Organization Apr 2020 ;(c) 2020 The authors; licensee World Health Organization. 2020 ;ISSN: 0042-9686 ;EISSN: 1564-0604 ;DOI: 10.2471/BLT.19.237636 ;PMID: 32284654

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11
Significance of natural language processing and chat-based generative language models
Significance of natural language processing and chat-based generative language models
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Significance of natural language processing and chat-based generative language models

Medizinische Klinik, Intensivmedizin und Notfallmedizin, 2024-04, Vol.119 (3), p.181

2023. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature. ;EISSN: 2193-6226 ;DOI: 10.1007/s00063-023-01098-5 ;PMID: 38108880

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12
Transfer learning enables predictions in network biology
Transfer learning enables predictions in network biology
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Transfer learning enables predictions in network biology

Nature (London), 2023-06, Vol.618 (7965), p.616 [Peer Reviewed Journal]

2023. The Author(s), under exclusive licence to Springer Nature Limited. ;EISSN: 1476-4687 ;DOI: 10.1038/s41586-023-06139-9 ;PMID: 37258680

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13
Forecasting stock prices with long-short term memory neural network based on attention mechanism
Forecasting stock prices with long-short term memory neural network based on attention mechanism
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Forecasting stock prices with long-short term memory neural network based on attention mechanism

PloS one, 2020-01, Vol.15 (1), p.e0227222-e0227222 [Peer Reviewed Journal]

COPYRIGHT 2020 Public Library of Science ;COPYRIGHT 2020 Public Library of Science ;2020 Qiu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Qiu et al 2020 Qiu et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0227222 ;PMID: 31899770

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14
Predicting COVID-19 in China Using Hybrid AI Model
Predicting COVID-19 in China Using Hybrid AI Model
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Predicting COVID-19 in China Using Hybrid AI Model

IEEE transactions on cybernetics, 2020-07, Vol.50 (7), p.2891 [Peer Reviewed Journal]

EISSN: 2168-2275 ;DOI: 10.1109/tcyb.2020.2990162 ;PMID: 32396126

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15
Drivers of the decrease of patent similarities from 1976 to 2021
Drivers of the decrease of patent similarities from 1976 to 2021
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Drivers of the decrease of patent similarities from 1976 to 2021

PloS one, 2023-03, Vol.18 (3), p.e0283247-e0283247 [Peer Reviewed Journal]

Copyright: © 2023 Filippi-Mazzola et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ;COPYRIGHT 2023 Public Library of Science ;2023 Filippi-Mazzola et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2023 Filippi-Mazzola et al 2023 Filippi-Mazzola et al ;2023 Filippi-Mazzola et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0283247 ;PMID: 36940211

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16
Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models
Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models
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Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models

Proceedings of the National Academy of Sciences - PNAS, 2020-10, Vol.117 (42), p.25966-25974 [Peer Reviewed Journal]

Copyright National Academy of Sciences Oct 20, 2020 ;2020 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.1910416117 ;PMID: 32989131

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17
Design considerations for a hierarchical semantic compositional framework for medical natural language understanding
Design considerations for a hierarchical semantic compositional framework for medical natural language understanding
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Design considerations for a hierarchical semantic compositional framework for medical natural language understanding

PloS one, 2023-03, Vol.18 (3), p.e0282882-e0282882 [Peer Reviewed Journal]

Copyright: © 2023 Taira et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ;COPYRIGHT 2023 Public Library of Science ;2023 Taira et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2023 Taira et al 2023 Taira et al ;2023 Taira et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0282882 ;PMID: 36928721

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18
Dynamic Embedding Projection-Gated Convolutional Neural Networks for Text Classification
Dynamic Embedding Projection-Gated Convolutional Neural Networks for Text Classification
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Dynamic Embedding Projection-Gated Convolutional Neural Networks for Text Classification

IEEE transaction on neural networks and learning systems, 2022-03, Vol.33 (3), p.973

EISSN: 2162-2388 ;DOI: 10.1109/TNNLS.2020.3036192 ;PMID: 33417564

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19
"What is relevant in a text document?": An interpretable machine learning approach
"What is relevant in a text document?": An interpretable machine learning approach
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"What is relevant in a text document?": An interpretable machine learning approach

PloS one, 2017-08, Vol.12 (8), p.e0181142-e0181142 [Peer Reviewed Journal]

COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Arras et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2017 Arras et al 2017 Arras et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0181142 ;PMID: 28800619

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20
Large-scale transportation network congestion evolution prediction using deep learning theory
Large-scale transportation network congestion evolution prediction using deep learning theory
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Large-scale transportation network congestion evolution prediction using deep learning theory

PloS one, 2015-03, Vol.10 (3), p.e0119044-e0119044 [Peer Reviewed Journal]

COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Ma et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2015 Ma et al 2015 Ma et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0119044 ;PMID: 25780910

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