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| Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
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| 1 |
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Correction for Li et al., Determining the nonequilibrium criticality of a Gardner transition via a hybrid study of molecular simulations and machine learningProceedings of the National Academy of Sciences - PNAS, 2022-09, Vol.119 (39), p.1-e2214479119 [Peer Reviewed Journal]Copyright National Academy of Sciences Sep 27, 2022 ;2022 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2214479119Full text available |
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Active learning machine learns to create new quantum experimentsProceedings of the National Academy of Sciences - PNAS, 2018-02, Vol.115 (6), p.1221-1226 [Peer Reviewed Journal]Volumes 1–89 and 106–114, copyright as a collective work only; author(s) retains copyright to individual articles ;Copyright National Academy of Sciences Feb 6, 2018 ;2018 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.1714936115 ;PMID: 29348200Full text available |
| 3 |
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The limitations of machine learning models for predicting scientific replicabilityProceedings of the National Academy of Sciences - PNAS, 2023-08, Vol.120 (33), p.e2307596120-e2307596120 [Peer Reviewed Journal]Copyright National Academy of Sciences Aug 15, 2023 ;Copyright © 2023 the Author(s). Published by PNAS. 2023 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2307596120 ;PMID: 37549293Full text available |
| 4 |
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Racial disparities in automated speech recognitionProceedings of the National Academy of Sciences - PNAS, 2020-04, Vol.117 (14), p.7684-7689 [Peer Reviewed Journal]Copyright © 2020 the Author(s). Published by PNAS. ;Copyright National Academy of Sciences Apr 7, 2020 ;Copyright © 2020 the Author(s). Published by PNAS. 2020 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.1915768117 ;PMID: 32205437Full text available |
| 5 |
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Reply to Crockett et al. and Mottelson and Kontogiorgos: Machine learning’s scientific significance and future impact on replicability researchProceedings of the National Academy of Sciences - PNAS, 2023-08, Vol.120 (33), p.1 [Peer Reviewed Journal]Copyright National Academy of Sciences Aug 15, 2023 ;Copyright © 2023 the Author(s). Published by PNAS. 2023 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2308195120Full text available |
| 6 |
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Recursive partitioning for heterogeneous causal effectsProceedings of the National Academy of Sciences - PNAS, 2016-07, Vol.113 (27), p.7353-7360 [Peer Reviewed Journal]Volumes 1–89 and 106–113, copyright as a collective work only; author(s) retains copyright to individual articles ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.1510489113 ;PMID: 27382149Full text available |
| 7 |
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Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectivenessBMJ (Online), 2020-03, Vol.368, p.l6927-l6927 [Peer Reviewed Journal]Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. ;2020 Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. BMJ This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/ . Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1756-1833 ;EISSN: 1756-1833 ;DOI: 10.1136/bmj.l6927 ;PMID: 32198138Full text available |
| 8 |
Material Type: Article
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Machine Learning–Based Model for Prediction of Outcomes in Acute StrokeStroke (1970), 2019-05, Vol.50 (5), p.1263-1265 [Peer Reviewed Journal]2019 American Heart Association, Inc. ;ISSN: 0039-2499 ;EISSN: 1524-4628 ;DOI: 10.1161/STROKEAHA.118.024293 ;PMID: 30890116Full text available |
| 9 |
Material Type: Article
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Ab initio thermodynamics of liquid and solid waterProceedings of the National Academy of Sciences - PNAS, 2019-01, Vol.116 (4), p.1110-1115 [Peer Reviewed Journal]Volumes 1–89 and 106–116, copyright as a collective work only; author(s) retains copyright to individual articles ;Copyright National Academy of Sciences Jan 22, 2019 ;2019 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.1815117116 ;PMID: 30610171Full text available |
| 10 |
Material Type: Article
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Leveraging Machine Learning and Artificial Intelligence to Improve Peripheral Artery Disease Detection, Treatment, and OutcomesCirculation research, 2021-06, Vol.128 (12), p.1833-1850 [Peer Reviewed Journal]ISSN: 0009-7330 ;EISSN: 1524-4571 ;DOI: 10.1161/circresaha.121.318224 ;PMID: 34110911Full text available |
| 11 |
Material Type: Article
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Cardiovascular Event Prediction by Machine Learning: The Multi-Ethnic Study of AtherosclerosisCirculation research, 2017-10, Vol.121 (9), p.1092-1101 [Peer Reviewed Journal]2017 American Heart Association, Inc. ;ISSN: 0009-7330 ;EISSN: 1524-4571 ;DOI: 10.1161/CIRCRESAHA.117.311312 ;PMID: 28794054Full text available |
| 12 |
Material Type: Article
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Bias and ethical considerations in machine learning and the automation of perioperative risk assessmentBritish journal of anaesthesia : BJA, 2020-12, Vol.125 (6), p.843-846 [Peer Reviewed Journal]2020 British Journal of Anaesthesia ;2020 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved. 2020 British Journal of Anaesthesia ;ISSN: 0007-0912 ;EISSN: 1471-6771 ;DOI: 10.1016/j.bja.2020.07.040 ;PMID: 32838979Full text available |
| 13 |
Material Type: Article
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Abstract 1231 Using Machine Learning to Predict Antimicrobial Resistance in Water-Derived E. coliThe Journal of biological chemistry, 2024-03, Vol.300 (3) [Peer Reviewed Journal]2024 The American Society for Biochemistry and Molecular Biology, Inc. ;ISSN: 0021-9258 ;EISSN: 1083-351X ;DOI: 10.1016/j.jbc.2024.105823Full text available |
| 14 |
Material Type: Article
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Correction to Supporting Information for Kim and Kim, Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning methodProceedings of the National Academy of Sciences - PNAS, 2021-01, Vol.118 (1), p.1 [Peer Reviewed Journal]Copyright National Academy of Sciences Jan 5, 2021 ;2021 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2024687118 ;PMID: 33318130Full text available |
| 15 |
Material Type: Article
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Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithmsProceedings of the National Academy of Sciences - PNAS, 2018-06, Vol.115 (24), p.6171-6176 [Peer Reviewed Journal]Volumes 1–89 and 106–114, copyright as a collective work only; author(s) retains copyright to individual articles ;Copyright © 2018 the Author(s). Published by PNAS. ;Copyright National Academy of Sciences Jun 12, 2018 ;Copyright © 2018 the Author(s). Published by PNAS. 2018 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.1721355115 ;PMID: 29844174Full text available |
| 16 |
Material Type: Article
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Machine learning classification can reduce false positives in structure-based virtual screeningProceedings of the National Academy of Sciences - PNAS, 2020-08, Vol.117 (31), p.18477-18488 [Peer Reviewed Journal]Copyright National Academy of Sciences Aug 4, 2020 ;Copyright © 2020 the Author(s). Published by PNAS. 2020 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.2000585117 ;PMID: 32669436Full text available |
| 17 |
Material Type: Article
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Clinical applications of machine learning algorithms: beyond the black boxBMJ (Online), 2019-03, Vol.364, p.l886-l886 [Peer Reviewed Journal]Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to ;Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go tohttp://group.bmj.com/group/rights-licensing/permissions2019BMJ ;ISSN: 0959-8138 ;EISSN: 1756-1833 ;DOI: 10.1136/bmj.l886 ;PMID: 30862612Full text available |
| 18 |
Material Type: Article
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Maternal blood transcriptome as a sensor of fetal organ maturation at the end of organogenesis in cattleinfo:eu-repo/semantics/OpenAccess ;ISSN: 0006-3363 ;EISSN: 1529-7268Digital Resources/Online E-Resources |
| 19 |
Material Type: Article
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Early prediction of mortality risk among patients with severe COVID-19, using machine learningInternational Journal of Epidemiology, 2021-01, Vol.49 (6), p.1918-1929 [Peer Reviewed Journal]The Author(s) 2020; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association 2020 ;The Author(s) 2020; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association. ;2020. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://academic.oup.com/journals/pages/coronavirus . ;ISSN: 0300-5771 ;EISSN: 1464-3685 ;DOI: 10.1093/ije/dyaa171 ;PMID: 32997743Digital Resources/Online E-Resources |
| 20 |
Material Type: Article
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A Shared Vision for Machine Learning in NeuroscienceThe Journal of neuroscience, 2018-02, Vol.38 (7), p.1601-1607 [Peer Reviewed Journal]Copyright © 2018 the authors 0270-6474/18/381601-07$15.00/0. ;Copyright © 2018 the authors 0270-6474/18/381601-07$15.00/0 2018 ;ISSN: 0270-6474 ;EISSN: 1529-2401 ;DOI: 10.1523/jneurosci.0508-17.2018 ;PMID: 29374138Full text available |
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