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The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation
The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation
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The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation

PeerJ. Computer science, 2021-07, Vol.7, p.e623-e623, Article e623 [Peer Reviewed Journal]

COPYRIGHT 2021 PeerJ. Ltd. ;2021 Chicco 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, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2021 Chicco et al. 2021 Chicco et al. ;ISSN: 2376-5992 ;EISSN: 2376-5992 ;DOI: 10.7717/peerj-cs.623 ;PMID: 34307865

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2
How good is the advice from ChatGPT for building science? Comparison of four scenarios
How good is the advice from ChatGPT for building science? Comparison of four scenarios
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How good is the advice from ChatGPT for building science? Comparison of four scenarios

Journal of physics. Conference series, 2023-11, Vol.2600 (8), p.82006 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/2600/8/082006

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3
Early prediction of mortality risk among patients with severe COVID-19, using machine learning
Early prediction of mortality risk among patients with severe COVID-19, using machine learning
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Early prediction of mortality risk among patients with severe COVID-19, using machine learning

International 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: 32997743

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4
A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis
A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis
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A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis

PloS one, 2021-02, Vol.16 (2), p.e0245909-e0245909 [Peer Reviewed Journal]

COPYRIGHT 2021 Public Library of Science ;COPYRIGHT 2021 Public Library of Science ;2021 Rustam 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. ;2021 Rustam et al 2021 Rustam et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0245909 ;PMID: 33630869

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5
A Survey on the Explainability of Supervised Machine Learning
A Survey on the Explainability of Supervised Machine Learning
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A Survey on the Explainability of Supervised Machine Learning

The Journal of artificial intelligence research, 2021-01, Vol.70, p.245-317 [Peer Reviewed Journal]

2021. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.jair.org/index.php/jair/about ;ISSN: 1076-9757 ;EISSN: 1943-5037 ;DOI: 10.1613/jair.1.12228

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6
Construction of a predictive model for blood transfusion in patients undergoing total hip arthroplasty and identification of clinical heterogeneity
Construction of a predictive model for blood transfusion in patients undergoing total hip arthroplasty and identification of clinical heterogeneity
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Construction of a predictive model for blood transfusion in patients undergoing total hip arthroplasty and identification of clinical heterogeneity

Scientific reports, 2024-01, Vol.14 (1), p.724-724, Article 724 [Peer Reviewed Journal]

2024. The Author(s). ;The Author(s) 2024. 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. ;The Author(s) 2024 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-024-51240-2 ;PMID: 38184749

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7
A Comprehensive Review on Machine Learning in Healthcare Industry: Classification, Restrictions, Opportunities and Challenges
A Comprehensive Review on Machine Learning in Healthcare Industry: Classification, Restrictions, Opportunities and Challenges
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A Comprehensive Review on Machine Learning in Healthcare Industry: Classification, Restrictions, Opportunities and Challenges

Sensors (Basel, Switzerland), 2023-04, Vol.23 (9), p.4178 [Peer Reviewed Journal]

COPYRIGHT 2023 MDPI AG ;2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://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. ;2023 by the authors. 2023 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s23094178 ;PMID: 37177382

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8
Retracted: A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19
Retracted: A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19
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Retracted: A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19

BioMed research international, 2024, Vol.2024, p.9879061-9879061 [Peer Reviewed Journal]

Copyright © 2024 BioMed Research International. ;Copyright © 2024 BioMed Research International. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 ;Copyright © 2024 BioMed Research International. 2024 ;ISSN: 2314-6133 ;EISSN: 2314-6141 ;DOI: 10.1155/2024/9879061 ;PMID: 38550152

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9
Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance
Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance
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Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance

Technologies (Basel), 2021-09, Vol.9 (3), p.52 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://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: 2227-7080 ;EISSN: 2227-7080 ;DOI: 10.3390/technologies9030052

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10
A Critical Review of Machine Learning Approaches for Predicting Diabetes Mellitus
A Critical Review of Machine Learning Approaches for Predicting Diabetes Mellitus
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A Critical Review of Machine Learning Approaches for Predicting Diabetes Mellitus

Cardiometry, 2023-03 (26), p.826-833 [Peer Reviewed Journal]

2023. This work is published under http://www.cardiometry.net/issues (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;EISSN: 2304-7232 ;DOI: 10.18137/cardiometry.2023.26.826833

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11
Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health risks classification
Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health risks classification
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Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health risks classification

BMC bioinformatics, 2024-03, Vol.25 (1), p.103-103 [Peer Reviewed Journal]

2024. The Author(s). ;COPYRIGHT 2024 BioMed Central Ltd. ;2024. 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. ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-024-05729-2 ;PMID: 38459463

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12
Prediction of diabetes disease using an ensemble of machine learning multi-classifier models
Prediction of diabetes disease using an ensemble of machine learning multi-classifier models
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Prediction of diabetes disease using an ensemble of machine learning multi-classifier models

BMC bioinformatics, 2023-09, Vol.24 (1), p.1-337, Article 337 [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. ;BioMed Central Ltd., part of Springer Nature 2023 ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-023-05465-z ;PMID: 37697283

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13
Realization of an Adaptive Test Paper Generation Function based on DPC Algorithm
Realization of an Adaptive Test Paper Generation Function based on DPC Algorithm
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Realization of an Adaptive Test Paper Generation Function based on DPC Algorithm

Journal of physics. Conference series, 2022-01, Vol.2171 (1), p.12056 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/2171/1/012056

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14
Federated Semi-Supervised Multi-Task Learning to Detect COVID-19 and Lungs Segmentation Marking Using Chest Radiography Images and Raspberry Pi Devices: An Internet of Medical Things Application
Federated Semi-Supervised Multi-Task Learning to Detect COVID-19 and Lungs Segmentation Marking Using Chest Radiography Images and Raspberry Pi Devices: An Internet of Medical Things Application
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Federated Semi-Supervised Multi-Task Learning to Detect COVID-19 and Lungs Segmentation Marking Using Chest Radiography Images and Raspberry Pi Devices: An Internet of Medical Things Application

Sensors (Basel, Switzerland), 2021-07, Vol.21 (15), p.5025 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://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. ;2021 by the authors. 2021 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s21155025 ;PMID: 34372262

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15
Identifying predictors of vaccination willingness and attitudes during Covid-19: Machine learning multi-country study
Identifying predictors of vaccination willingness and attitudes during Covid-19: Machine learning multi-country study
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Identifying predictors of vaccination willingness and attitudes during Covid-19: Machine learning multi-country study

European psychiatry, 2023-03, Vol.66 (S1), p.S410-S410 [Peer Reviewed Journal]

The Author(s), 2023. Published by Cambridge University Press on behalf of the European Psychiatric Association. This work is licensed under the Creative Commons Attribution License This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. (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 2023 The Author(s) ;ISSN: 0924-9338 ;EISSN: 1778-3585 ;DOI: 10.1192/j.eurpsy.2023.884

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16
Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions
Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions
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Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions

International journal of environmental research and public health, 2021-01, Vol.18 (3), p.1117 [Peer Reviewed Journal]

2021. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2021 by the authors. 2021 ;ISSN: 1660-4601 ;ISSN: 1661-7827 ;EISSN: 1660-4601 ;DOI: 10.3390/ijerph18031117 ;PMID: 33513984

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17
Multi-Label Active Learning-Based Machine Learning Model for Heart Disease Prediction
Multi-Label Active Learning-Based Machine Learning Model for Heart Disease Prediction
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Multi-Label Active Learning-Based Machine Learning Model for Heart Disease Prediction

Sensors (Basel, Switzerland), 2022-02, Vol.22 (3), p.1184 [Peer Reviewed Journal]

COPYRIGHT 2022 MDPI AG ;2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://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. ;2022 by the authors. 2022 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s22031184 ;PMID: 35161928

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18
Why do people oppose mask wearing? A comprehensive analysis of U.S. tweets during the COVID-19 pandemic
Why do people oppose mask wearing? A comprehensive analysis of U.S. tweets during the COVID-19 pandemic
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Why do people oppose mask wearing? A comprehensive analysis of U.S. tweets during the COVID-19 pandemic

Journal of the American Medical Informatics Association, 2021-07, Vol.28 (7), p.1564-1573 [Peer Reviewed Journal]

The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com 2021 ;The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com. ;2021. 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: 1527-974X ;ISSN: 1067-5027 ;EISSN: 1527-974X ;DOI: 10.1093/jamia/ocab047 ;PMID: 33690794

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19
Retracted: Machine Learning Model and Statistical Methods for COVID-19 Evolution Prediction
Retracted: Machine Learning Model and Statistical Methods for COVID-19 Evolution Prediction
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Retracted: Machine Learning Model and Statistical Methods for COVID-19 Evolution Prediction

Wireless communications and mobile computing, 2023-12, Vol.2023, p.1-1 [Peer Reviewed Journal]

Copyright © 2023 Wireless Communications and Mobile Computing. ;Copyright © 2023 Wireless Communications and Mobile Computing. 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. ;ISSN: 1530-8669 ;EISSN: 1530-8677 ;DOI: 10.1155/2023/9814036

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20
Exploring U.S. Shifts in Anti-Asian Sentiment with the Emergence of COVID-19
Exploring U.S. Shifts in Anti-Asian Sentiment with the Emergence of COVID-19
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Exploring U.S. Shifts in Anti-Asian Sentiment with the Emergence of COVID-19

International journal of environmental research and public health, 2020-09, Vol.17 (19), p.7032 [Peer Reviewed Journal]

2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (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. ;2020 by the authors. 2020 ;ISSN: 1660-4601 ;ISSN: 1661-7827 ;EISSN: 1660-4601 ;DOI: 10.3390/ijerph17197032 ;PMID: 32993005

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