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Material Type: Article
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The State of the Art in Enhancing Trust in Machine Learning Models with the Use of VisualizationsComputer graphics forum, 2020-06, Vol.39 (3), p.713-756 [Peer Reviewed Journal]Attribution ;ISSN: 0167-7055 ;EISSN: 1467-8659 ;DOI: 10.1111/cgf.14034Digital Resources/Online E-Resources |
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Material Type: Conference Proceeding
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CC2Vec: Distributed Representations of Code ChangesDistributed under a Creative Commons Attribution 4.0 International License ;DOI: 10.1145/3377811.3380361Digital Resources/Online E-Resources |
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Material Type: Article
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A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAIIEEE transaction on neural networks and learning systems, 2021-11, Vol.32 (11), p.4793-4813ISSN: 2162-237X ;EISSN: 2162-2388 ;DOI: 10.1109/TNNLS.2020.3027314 ;PMID: 33079674 ;CODEN: ITNNALDigital Resources/Online E-Resources |
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Material Type: Article
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Multi-Input data ASsembly for joint AnalysisPloS one, 2024-05, Vol.19 (5), p.e0302425 [Peer Reviewed Journal]COPYRIGHT 2024 Public Library of Science ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0302425Full text available |
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Material Type: Article
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Correction: Impacts of multicollinearity on CAPT modalities: An heterogeneous machine learning framework for computer-assisted French phoneme pronunciation trainingPloS one, 2023-10, Vol.18 (10), p.e0292513-e0292513 [Peer Reviewed Journal]COPYRIGHT 2023 Public Library of Science ;2023 Bi 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 Bi et al 2023 Bi et al ;2023 Bi 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.0292513Full text available |
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Material Type: Article
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A Machine Learning Model Based on GRU and LSTM to Predict the Environmental Parameters in a Layer House, Taking CO[sub.2] Concentration as an ExampleSensors (Basel, Switzerland), 2023-12, Vol.24 (1) [Peer Reviewed Journal]COPYRIGHT 2023 MDPI AG ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s24010244Full text available |
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Material Type: Article
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Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow ProblemsWater resources research, 2020-05, Vol.56 (5), p.n/a [Peer Reviewed Journal]2020. American Geophysical Union. All Rights Reserved. ;ISSN: 0043-1397 ;EISSN: 1944-7973 ;DOI: 10.1029/2019WR026731Full text available |
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Material Type: Article
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Peering Into the Black Box of Artificial Intelligence: Evaluation Metrics of Machine Learning MethodsAmerican journal of roentgenology (1976), 2019-01, Vol.212 (1), p.38-43 [Peer Reviewed Journal]ISSN: 0361-803X ;EISSN: 1546-3141 ;DOI: 10.2214/AJR.18.20224 ;PMID: 30332290Full text available |
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Material Type: Article
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Correction: A hybrid machine learning framework to improve prediction of all-cause rehospitalization among eldely patients in Hong KongBMC medical research methodology, 2023-02, Vol.23 (1), p.38-38, Article 38 [Peer Reviewed Journal]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: 1471-2288 ;EISSN: 1471-2288 ;DOI: 10.1186/s12874-023-01851-6 ;PMID: 36782144Full text available |
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Material Type: Article
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GPT-4 is here: what scientists thinkNature (London), 2023-03, Vol.615 (7954), p.773-773 [Peer Reviewed Journal]ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/d41586-023-00816-5 ;PMID: 36928404Full text available |
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Material Type: Article
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Mastering the game of Go without human knowledgeNature (London), 2017-10, Vol.550 (7676), p.354-359 [Peer Reviewed Journal]COPYRIGHT 2017 Nature Publishing Group ;COPYRIGHT 2017 Nature Publishing Group ;Copyright Nature Publishing Group Oct 19, 2017 ;ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/nature24270 ;PMID: 29052630Full text available |
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Material Type: Article
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Correction to "Machine Learning-Based Prediction of Elevated PTH Levels Among the US General Population"The journal of clinical endocrinology and metabolism, 2023-01, Vol.108 (2), p.e29-e29 [Peer Reviewed Journal]COPYRIGHT 2023 Oxford University Press ;ISSN: 0021-972X ;EISSN: 1945-7197 ;DOI: 10.1210/clinem/dgac676 ;PMID: 36451340Full text available |
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Material Type: Article
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This AI researcher is trying to ward off a reproducibility crisisNature, 2020-01, Vol.577 (7788), p.14-14 [Peer Reviewed Journal]ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/d41586-019-03895-5 ;PMID: 31871325Full text available |
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Material Type: Article
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Deep learning: new computational modelling techniques for genomicsNature reviews. Genetics, 2019-07, Vol.20 (7), p.389-403 [Peer Reviewed Journal]COPYRIGHT 2019 Nature Publishing Group ;COPYRIGHT 2019 Nature Publishing Group ;Springer Nature Limited 2019. ;ISSN: 1471-0056 ;EISSN: 1471-0064 ;DOI: 10.1038/s41576-019-0122-6 ;PMID: 30971806Full text available |
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Material Type: Article
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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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Material Type: Article
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How Important Is Satellite-Retrieved Aerosol Optical Depth in Deriving Surface PM[sub.2.5] Using Machine Learning?Remote sensing (Basel, Switzerland), 2023-07, Vol.15 (15) [Peer Reviewed Journal]COPYRIGHT 2023 MDPI AG ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs15153780Full text available |
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Material Type: Article
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Do no harm: a roadmap for responsible machine learning for health careNature medicine, 2019-09, Vol.25 (9), p.1337-1340 [Peer Reviewed Journal]COPYRIGHT 2019 Nature Publishing Group ;COPYRIGHT 2019 Nature Publishing Group ;Copyright Nature Publishing Group Sep 2019 ;ISSN: 1078-8956 ;EISSN: 1546-170X ;DOI: 10.1038/s41591-019-0548-6 ;PMID: 31427808Full text available |
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Material Type: Article
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Machine Learning in Psychometrics and Psychological ResearchFrontiers in psychology, 2020-01, Vol.10, p.2970-2970 [Peer Reviewed Journal]Copyright © 2020 Orrù, Monaro, Conversano, Gemignani and Sartori. ;Copyright © 2020 Orrù, Monaro, Conversano, Gemignani and Sartori. 2020 Orrù, Monaro, Conversano, Gemignani and Sartori ;ISSN: 1664-1078 ;EISSN: 1664-1078 ;DOI: 10.3389/fpsyg.2019.02970 ;PMID: 31998200Full text available |
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Material Type: Article
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Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s NextJournal of scientific computing, 2022-09, Vol.92 (3), p.88, Article 88 [Peer Reviewed Journal]The Author(s) 2022 ;The Author(s) 2022. This work is published 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. ;ISSN: 0885-7474 ;EISSN: 1573-7691 ;DOI: 10.1007/s10915-022-01939-zFull text available |
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Material Type: Article
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In AI, is bigger always better?Nature (London), 2023-03, Vol.615 (7951), p.202-205 [Peer Reviewed Journal]ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/d41586-023-00641-w ;PMID: 36890378Full text available |