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1
Machine learning for comprehensive forecasting of Alzheimer's Disease progression
Machine learning for comprehensive forecasting of Alzheimer's Disease progression
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Machine learning for comprehensive forecasting of Alzheimer's Disease progression

Scientific reports, 2019-09, Vol.9 (1), p.13622-14, Article 13622 [Peer Reviewed Journal]

2019. 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) 2019 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-019-49656-2 ;PMID: 31541187

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2
Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment
Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment
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Accuracy of deep learning, a machine-learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment

Scientific reports, 2017-08, Vol.7 (1), p.9425-4, Article 9425 [Peer Reviewed Journal]

2017. 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) 2017 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-017-09891-x ;PMID: 28842613

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3
A machine learning model for predicting surgical intervention in renal colic due to ureteral stone(s) < 5 mm
A machine learning model for predicting surgical intervention in renal colic due to ureteral stone(s) < 5 mm
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A machine learning model for predicting surgical intervention in renal colic due to ureteral stone(s) < 5 mm

Scientific reports, 2022-07, Vol.12 (1), p.11788-11788, Article 11788 [Peer Reviewed Journal]

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. ;The Author(s) 2022 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-022-16128-z ;PMID: 35821517

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4
African soil properties and nutrients mapped at 30&#160;m spatial resolution using two-scale ensemble machine learning
African soil properties and nutrients mapped at 30&#160;m spatial resolution using two-scale ensemble machine learning
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African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning

Scientific reports, 2021-03, Vol.11 (1), p.6130-6130, Article 6130 [Peer Reviewed Journal]

The Author(s) 2021. 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) 2021 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-021-85639-y ;PMID: 33731749

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5
Predicting the Young's Modulus of Silicate Glasses using High-Throughput Molecular Dynamics Simulations and Machine Learning
Predicting the Young's Modulus of Silicate Glasses using High-Throughput Molecular Dynamics Simulations and Machine Learning
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Predicting the Young's Modulus of Silicate Glasses using High-Throughput Molecular Dynamics Simulations and Machine Learning

Scientific reports, 2019-06, Vol.9 (1), p.8739-11, Article 8739 [Peer Reviewed Journal]

2019. 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) 2019 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-019-45344-3 ;PMID: 31217500

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6
Development and validation of a hybrid deep learning&#8211;machine learning approach for severity assessment of COVID-19 and other pneumonias
Development and validation of a hybrid deep learning&#8211;machine learning approach for severity assessment of COVID-19 and other pneumonias
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Development and validation of a hybrid deep learning–machine learning approach for severity assessment of COVID-19 and other pneumonias

Scientific reports, 2023-08, Vol.13 (1), p.13420-13420, Article 13420 [Peer Reviewed Journal]

The Author(s) 2023. 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. ;Springer Nature Limited 2023 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-023-40506-w ;PMID: 37591967

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7
A multipurpose machine learning approach to predict COVID-19 negative prognosis in S&#227;o Paulo, Brazil
A multipurpose machine learning approach to predict COVID-19 negative prognosis in S&#227;o Paulo, Brazil
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A multipurpose machine learning approach to predict COVID-19 negative prognosis in São Paulo, Brazil

Scientific reports, 2021-02, Vol.11 (1), p.3343-3343, Article 3343 [Peer Reviewed Journal]

The Author(s) 2021. 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) 2021 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-021-82885-y ;PMID: 33558602

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8
Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease
Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease
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Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease

Scientific reports, 2018-05, Vol.8 (1), p.7129-21, Article 7129 [Peer Reviewed Journal]

2018. 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) 2018 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-018-24783-4 ;PMID: 29740058

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9
Disentangling Jenny&#8217;s equation by machine learning
Disentangling Jenny&#8217;s equation by machine learning
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Disentangling Jenny’s equation by machine learning

Scientific reports, 2023-11, Vol.13 (1), p.20916-20916, Article 20916 [Peer Reviewed Journal]

The Author(s) 2023. 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) 2023 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-023-44171-x ;PMID: 38017030

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10
Predictive Modeling of the Hospital Readmission Risk from Patients' Claims Data Using Machine Learning: A Case Study on COPD
Predictive Modeling of the Hospital Readmission Risk from Patients' Claims Data Using Machine Learning: A Case Study on COPD
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Predictive Modeling of the Hospital Readmission Risk from Patients' Claims Data Using Machine Learning: A Case Study on COPD

Scientific reports, 2019-02, Vol.9 (1), p.2362-2362, Article 2362 [Peer Reviewed Journal]

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) 2019 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-019-39071-y ;PMID: 30787351

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11
Prediction of SMEs' R&amp;D performances by machine learning for project selection
Prediction of SMEs' R&amp;D performances by machine learning for project selection
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Prediction of SMEs' R&D performances by machine learning for project selection

Scientific reports, 2023-05, Vol.13 (1), p.7598-7598, Article 7598 [Peer Reviewed Journal]

2023. The Author(s). ;The Author(s) 2023. 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) 2023 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-023-34684-w ;PMID: 37165080

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12
Machine learning assisted prediction of the Young's modulus of compositionally complex alloys
Machine learning assisted prediction of the Young's modulus of compositionally complex alloys
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Machine learning assisted prediction of the Young's modulus of compositionally complex alloys

Scientific reports, 2021-08, Vol.11 (1), p.17149-17149, Article 17149 [Peer Reviewed Journal]

2021. The Author(s). ;The Author(s) 2021. 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) 2021 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-021-96507-0 ;PMID: 34433841

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13
Discriminating cognitive status in Parkinson's disease through functional connectomics and machine learning
Discriminating cognitive status in Parkinson's disease through functional connectomics and machine learning
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Discriminating cognitive status in Parkinson's disease through functional connectomics and machine learning

Scientific reports, 2017-03, Vol.7 (1), p.45347-45347, Article 45347 [Peer Reviewed Journal]

Copyright Nature Publishing Group Mar 2017 ;cc-by (c) Abós, Alexandra et al., 2017 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/3.0/es ;Copyright © 2017, The Author(s) 2017 The Author(s) ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/srep45347 ;PMID: 28349948

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14
Forecasting medical state&#160;transition using machine learning methods
Forecasting medical state&#160;transition using machine learning methods
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Forecasting medical state transition using machine learning methods

Scientific reports, 2022-11, Vol.12 (1), p.20478-20478, Article 20478 [Peer Reviewed Journal]

2022. The Author(s). ;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. ;The Author(s) 2022 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-022-24408-x ;PMID: 36443331

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15
A machine learning framework for predicting drug&#8211;drug interactions
A machine learning framework for predicting drug&#8211;drug interactions
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A machine learning framework for predicting drug–drug interactions

Scientific reports, 2021-09, Vol.11 (1), p.17619-17619, Article 17619 [Peer Reviewed Journal]

The Author(s) 2021. 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) 2021 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-021-97193-8 ;PMID: 34475500

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16
Selecting Clinically Relevant Gait Characteristics for Classification of Early Parkinson's Disease: A Comprehensive Machine Learning Approach
Selecting Clinically Relevant Gait Characteristics for Classification of Early Parkinson's Disease: A Comprehensive Machine Learning Approach
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Selecting Clinically Relevant Gait Characteristics for Classification of Early Parkinson's Disease: A Comprehensive Machine Learning Approach

Scientific reports, 2019-11, Vol.9 (1), p.17269-12, Article 17269 [Peer Reviewed Journal]

2019. 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) 2019 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-019-53656-7 ;PMID: 31754175

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17
Divorce prediction using machine learning algorithms in Ha'il region, KSA
Divorce prediction using machine learning algorithms in Ha'il region, KSA
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Divorce prediction using machine learning algorithms in Ha'il region, KSA

Scientific reports, 2024-01, Vol.14 (1), p.502-502, Article 502 [Peer Reviewed Journal]

2024. The Author(s). ;The Author(s) 2024. corrected publication 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. ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-023-50839-1 ;PMID: 38177210

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18
Identification of metabolic pathways contributing to ER + breast cancer disparities using a machine-learning pipeline
Identification of metabolic pathways contributing to ER + breast cancer disparities using a machine-learning pipeline
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Identification of metabolic pathways contributing to ER + breast cancer disparities using a machine-learning pipeline

Scientific reports, 2023-07, Vol.13 (1), p.12136-12136 [Peer Reviewed Journal]

2023. The Author(s). ;The Author(s) 2023. 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) 2023 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-023-39215-1 ;PMID: 37495653

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19
Classification of Parkinson&#8217;s disease and its stages using machine learning
Classification of Parkinson&#8217;s disease and its stages using machine learning
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Article 		Add to My Research

Classification of Parkinson’s disease and its stages using machine learning

Scientific reports, 2022-08, Vol.12 (1), p.14036-14036, Article 14036 [Peer Reviewed Journal]

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. ;The Author(s) 2022 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-022-18015-z ;PMID: 35982070

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20
An explainable machine learning approach for Alzheimer's disease classification
An explainable machine learning approach for Alzheimer's disease classification
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An explainable machine learning approach for Alzheimer's disease classification

Scientific reports, 2024-02, Vol.14 (1), p.2637-2637, Article 2637 [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. ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-024-51985-w ;PMID: 38302557

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