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For: Chadaga K, Chakraborty C, Prabhu S, Umakanth S, Bhat V, Sampathila N. Clinical and Laboratory Approach to Diagnose COVID-19 Using Machine Learning. Interdiscip Sci 2022;14:452-70. [PMID: 35133633 DOI: 10.1007/s12539-021-00499-4] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Deebak BD, Al-turjman F. EEI-IoT: Edge-Enabled Intelligent IoT Framework for Early Detection of COVID-19 Threats. Sensors 2023;23:2995. [DOI: 10.3390/s23062995] [Reference Citation Analysis]
2 Behnoush AH, Khalaji A, Rezaee M, Momtahen S, Mansourian S, Bagheri J, Masoudkabir F, Hosseini K. Machine learning-based prediction of 1-year mortality in hypertensive patients undergoing coronary revascularization surgery. Clin Cardiol 2023;46:269-78. [PMID: 36588391 DOI: 10.1002/clc.23963] [Reference Citation Analysis]
3 Askari Nasab K, Mirzaei J, Zali A, Gholizadeh S, Akhlaghdoust M. Coronavirus diagnosis using cough sounds: Artificial intelligence approaches. Front Artif Intell 2023;6:1100112. [PMID: 36872932 DOI: 10.3389/frai.2023.1100112] [Reference Citation Analysis]
4 Sharma A, Mishra PK. Covid-MANet: Multi-task attention network for explainable diagnosis and severity assessment of COVID-19 from CXR images. Pattern Recognit 2022;131:108826. [PMID: 35698723 DOI: 10.1016/j.patcog.2022.108826] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
5 Ayadi M, Ksibi A, Al-rasheed A, Soufiene BO. COVID-AleXception: A Deep Learning Model Based on a Deep Feature Concatenation Approach for the Detection of COVID-19 from Chest X-ray Images. Healthcare 2022;10:2072. [DOI: 10.3390/healthcare10102072] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Chadaga K, Prabhu S, K VB, Sampathila N, Umakanth S, Chadaga R. COVID-19 Mortality Prediction using Machine Learning: A Deep Forest Approach. 2022 International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics ( DISCOVER) 2022. [DOI: 10.1109/discover55800.2022.9974666] [Reference Citation Analysis]
7 Pradhan A, Prabhu S, Chadaga K, Sengupta S, Nath G. Supervised Learning Models for the Preliminary Detection of COVID-19 in Patients Using Demographic and Epidemiological Parameters. Information 2022;13:330. [DOI: 10.3390/info13070330] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
8 Heidari A, Jafari Navimipour N, Unal M, Toumaj S. Machine learning applications for COVID-19 outbreak management. Neural Comput Appl 2022;:1-36. [PMID: 35702664 DOI: 10.1007/s00521-022-07424-w] [Cited by in Crossref: 7] [Cited by in F6Publishing: 10] [Article Influence: 7.0] [Reference Citation Analysis]
9 Mohammedqasem R, Mohammedqasim H, Ata O. Real-time data of COVID-19 detection with IoT sensor tracking using artificial neural network. Comput Electr Eng 2022;100:107971. [PMID: 35399912 DOI: 10.1016/j.compeleceng.2022.107971] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]