For: | Chen MJ, Yang PH, Hsieh MT, Yeh CH, Huang CH, Yang CM, Lin GM. Machine learning to relate PM2.5 and PM10 concentrations to outpatient visits for upper respiratory tract infections in Taiwan: A nationwide analysis. World J Clin Cases 2018; 6(8): 200-206 [PMID: 30148148 DOI: 10.12998/wjcc.v6.i8.200] |
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URL: | https://www.wjgnet.com/2307-8960/full/v6/i8/200.htm |
Number | Citing Articles |
1 |
Yi He, Wanyanhan Jiang, Xi Gao, Chengwei Lin, Jia Li, Lian Yang. Short-term effects and economic burden of air pollutants on acute lower respiratory tract infections in children in Southwest China: a time-series study. Environmental Health 2023; 22(1) doi: 10.1186/s12940-023-00962-3
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2 |
Daitao Zhang, Yaohua Tian, Yi Zhang, Yaying Cao, Quanyi Wang, Yonghua Hu. Fine Particulate Air Pollution and Hospital Utilization for Upper Respiratory Tract Infections in Beijing, China. International Journal of Environmental Research and Public Health 2019; 16(4): 533 doi: 10.3390/ijerph16040533
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3 |
Ruirui Liang, Yi Lu, Xiaosheng Qu, Qiang Su, Chunxia Li, Sijing Xia, Yongxin Liu, Qiang Zhang, Xin Cao, Qin Chen, Bing Niu. Prediction for global African swine fever outbreaks based on a combination of random forest algorithms and meteorological data. Transboundary and Emerging Diseases 2020; 67(2): 935 doi: 10.1111/tbed.13424
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4 |
Gen-Min Lin, Kiang Liu. An Electrocardiographic System With Anthropometrics via Machine Learning to Screen Left Ventricular Hypertrophy among Young Adults. IEEE Journal of Translational Engineering in Health and Medicine 2020; 8: 1 doi: 10.1109/JTEHM.2020.2990073
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5 |
Gen-Min Lin, Henry Horng-Shing Lu. Electrocardiographic Machine Learning to Predict Left Ventricular Diastolic Dysfunction in Asian Young Male Adults. IEEE Access 2021; 9: 49047 doi: 10.1109/ACCESS.2021.3069232
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6 |
Sing-Ling Jhuo, Mi -Tren Hsieh, Ting-Chien Weng, Mei-Juan Chen, Chieh-Ming Yang, Chia-Hung Yeh. Trend Prediction of Influenza and the Associated Pneumonia in Taiwan Using Machine Learning. 2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) 2019; : 1 doi: 10.1109/ISPACS48206.2019.8986244
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7 |
Gen-Min Lin, Henry Horng-Shing Lu. A 12-Lead ECG-Based System With Physiological Parameters and Machine Learning to Identify Right Ventricular Hypertrophy in Young Adults. IEEE Journal of Translational Engineering in Health and Medicine 2020; 8: 1 doi: 10.1109/JTEHM.2020.2996370
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8 |
Chu-Yu Hsu, Pang-Yen Liu, Shu-Hsin Liu, Younghoon Kwon, Carl J. Lavie, Gen-Min Lin. Machine Learning for Electrocardiographic Features to Identify Left Atrial Enlargement in Young Adults: CHIEF Heart Study. Frontiers in Cardiovascular Medicine 2022; 9 doi: 10.3389/fcvm.2022.840585
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9 |
Shaon Hossain Sani, Akramkhan Rony, Fyruz Ibnat Karim, M. F. Mridha, Md. Abdul Hamid. International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing 2021; 1166: 771 doi: 10.1007/978-981-15-5148-2_67
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10 |
Jue Tao Lim, Kelvin Bryan Tan, John Abisheganaden, Borame L. Dickens, Virginia E. Pitzer. Forecasting upper respiratory tract infection burden using high-dimensional time series data and forecast combinations. PLOS Computational Biology 2023; 19(2): e1010892 doi: 10.1371/journal.pcbi.1010892
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11 |
Amitesh Gupta, Md Moniruzzaman, Avinash Hande, Iman Rousta, Haraldur Olafsson, Karno Kumar Mondal. Estimation of particulate matter (PM2.5, PM10) concentration and its variation over urban sites in Bangladesh. SN Applied Sciences 2020; 2(12) doi: 10.1007/s42452-020-03829-1
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12 |
Gen-Min Lin, Huan-Chang Zeng. Electrocardiographic Machine Learning to Predict Mitral Valve Prolapse in Young Adults. IEEE Access 2021; 9: 103132 doi: 10.1109/ACCESS.2021.3098039
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13 |
Disha Shah, Bhavarth Dave, Mehul R. Chorawala, Bhupendra G. Prajapati, Sudarshan Singh, Gehan M. Elossaily, Mohd Nazam Ansari, Nemat Ali. An Insight on Microfluidic Organ-on-a-Chip Models for PM2.5-Induced Pulmonary Complications. ACS Omega 2024; 9(12): 13534 doi: 10.1021/acsomega.3c10271
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14 |
Dilip Kumar Mahato, Balram Ambade, Tushar Choudhary, Alaa M. Younis, Abdullah H. Alluhayb. Quantifying the Impact of Haze and Normal Air Quality on Urban Environments: A Study of Diurnal Variation, Source Apportionment, and Correlation. Water, Air, & Soil Pollution 2024; 235(12) doi: 10.1007/s11270-024-07579-3
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15 |
Chia-Ju Ellen Chi, Daniel Zinsmeister, I-Ling Lai, Shih-Chieh Chang, Yau-Lun Kuo, Jürgen Burkhardt. Aerosol Impacts on Water Relations of Camphor (Cinnamomum camphora). Frontiers in Plant Science 2022; 13 doi: 10.3389/fpls.2022.892096
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16 |
Amjad Alkhodaidi, Afraa Attiah, Alaa Mhawish, Abeer Hakeem. The Role of Machine Learning in Enhancing Particulate Matter Estimation: A Systematic Literature Review. Technologies 2024; 12(10): 198 doi: 10.3390/technologies12100198
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17 |
Hao Zhou, Tianqi Wang, Fang Zhou, Ye Liu, Weiqing Zhao, Xike Wang, Heng Chen, Yuxia Cui. Ambient Air Pollution and Daily Hospital Admissions for Respiratory Disease in Children in Guiyang, China. Frontiers in Pediatrics 2019; 7 doi: 10.3389/fped.2019.00400
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18 |
Bing Niu, Ruirui Liang, Guangya Zhou, Qiang Zhang, Qiang Su, Xiaosheng Qu, Qin Chen. Prediction for Global Peste des Petits Ruminants Outbreaks Based on a Combination of Random Forest Algorithms and Meteorological Data. Frontiers in Veterinary Science 2021; 7 doi: 10.3389/fvets.2020.570829
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19 |
Kelly S. Peterson, Alec B. Chapman, Wathsala Widanagamaachchi, Jesse Sutton, Brennan Ochoa, Barbara E. Jones, Vanessa Stevens, David C. Classen, Makoto M. Jones, Hualou Liang. Automating detection of diagnostic error of infectious diseases using machine learning. PLOS Digital Health 2024; 3(6): e0000528 doi: 10.1371/journal.pdig.0000528
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20 |
Yijing Feng, Edgar Castro, Yaguang Wei, Tingfan Jin, Xinye Qiu, Francesca Dominici, Joel Schwartz. Long-term exposure to ambient PM2.5, particulate constituents and hospital admissions from non-respiratory infection. Nature Communications 2024; 15(1) doi: 10.1038/s41467-024-45776-0
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21 |
Achraf Qor-el-aine, András Béres, Gábor Géczi. Calibration of CAMS PM2.5 data over Hungary: a machine learning approach. Environmental Research Communications 2024; 6(7): 075026 doi: 10.1088/2515-7620/ad6239
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22 |
Susymary Johnson, Deepalakshmi Perumalsamy. Application of XGBoost algorithm and grid search hyperparameter tuning to study health effects among individuals in the industrial area. Multimedia Tools and Applications 2025; doi: 10.1007/s11042-024-20592-2
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23 |
Muhammad Subhanullah, Nazim Hassan, Gouhar Rahman, Bakht Rawan, Waheed Ullah, Muhammad Ilyas. Concentration of Particulate Matter and Its Impact on Public Health in Different Cities in Pakistan-A Review. Environmental Forensics 2025; 26(2): 146 doi: 10.1080/15275922.2024.2366794
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24 |
Yan Liu, Yangyang Geng, Liuqing Yang, Shate Xiang, Qiaotong Wang, Lanyawen Hu, Ping Ye. Traditional Chinese Medicine Constitution and Clinical Data Association with Machine Learning for Prediction of Spontaneous Abortion. Clinical Complementary Medicine and Pharmacology 2022; 2(2): 100016 doi: 10.1016/j.ccmp.2021.100016
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25 |
Bahram Choubin, Mahsa Abdolshahnejad, Ehsan Moradi, Xavier Querol, Amir Mosavi, Shahaboddin Shamshirband, Pedram Ghamisi. Spatial hazard assessment of the PM10 using machine learning models in Barcelona, Spain. Science of The Total Environment 2020; 701: 134474 doi: 10.1016/j.scitotenv.2019.134474
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26 |
Alaa Mhawish, Tirthankar Banerjee, Meytar Sorek-Hamer, Muhammad Bilal, Alexei I. Lyapustin, Robert Chatfield, David M. Broday. Estimation of High-Resolution PM2.5 over the Indo-Gangetic Plain by Fusion of Satellite Data, Meteorology, and Land Use Variables. Environmental Science & Technology 2020; 54(13): 7891 doi: 10.1021/acs.est.0c01769
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27 |
Daniel P. Croft, Mark J. Utell, Han Liu, Shao Lin, Philip K. Hopke, Sally W. Thurston, Yunle Chen, David Q. Rich. Change in rate of healthcare encounters for respiratory infection from air pollution exposure after improved vehicle emissions standards in New York State. Air Quality, Atmosphere & Health 2024; 17(6): 1267 doi: 10.1007/s11869-024-01505-6
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28 |
Gen-Min Lin, Masanori Nagamine, Szu-Nian Yang, Yueh-Ming Tai, Chin Lin, Hiroshi Sato. Machine Learning Based Suicide Ideation Prediction for Military Personnel. IEEE Journal of Biomedical and Health Informatics 2020; 24(7): 1907 doi: 10.1109/JBHI.2020.2988393
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29 |
Sawaeng Kawichai, Patumrat Sripan, Amaraporn Rerkasem, Kittipan Rerkasem, Worawut Srisukkham. Long-Term Retrospective Predicted Concentration of PM2.5 in Upper Northern Thailand Using Machine Learning Models. Toxics 2025; 13(3): 170 doi: 10.3390/toxics13030170
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