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For: Chowdhury NK, Kabir MA, Rahman MM, Islam SMS. Machine learning for detecting COVID-19 from cough sounds: An ensemble-based MCDM method. Comput Biol Med 2022;145:105405. [PMID: 35318171 DOI: 10.1016/j.compbiomed.2022.105405] [Cited by in Crossref: 14] [Cited by in F6Publishing: 11] [Article Influence: 14.0] [Reference Citation Analysis]
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1 Zhang J, Wu J, Qiu Y, Song A, Li W, Li X, Liu Y. Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review. Comput Biol Med 2023;153:106517. [PMID: 36623438 DOI: 10.1016/j.compbiomed.2022.106517] [Reference Citation Analysis]
2 Najaran MHT. An evolutionary ensemble learning for diagnosing COVID-19 via cough signals. Intell Med 2023. [PMID: 36743333 DOI: 10.1016/j.imed.2023.01.001] [Reference Citation Analysis]
3 Jafarzadeh Ghoushchi S, Bonab SR, Ghiaci AM. A decision-making framework for COVID-19 infodemic management strategies evaluation in spherical fuzzy environment. Stoch Environ Res Risk Assess 2023;:1-14. [PMID: 36714449 DOI: 10.1007/s00477-022-02355-3] [Reference Citation Analysis]
4 Linh NH, Phong PD, Muthumaralingam T, Tan TM, Danh TH, Pi VN, Tu HX, Van Tung N. Determination of Best Input Factors for PMEDM 90CrSi Tool Steel Using MABAC Method. Advances in Engineering Research and Application 2023. [DOI: 10.1007/978-3-031-22200-9_36] [Reference Citation Analysis]
5 Rahman S, Sofi SA, Parveen S, Zahoor S. Medical Internet of Things and Data Analytics for Post-COVID Care: An Analysis. Intelligent Data Engineering and Analytics 2023. [DOI: 10.1007/978-981-19-7524-0_14] [Reference Citation Analysis]
6 Anibal JT, Landa AJ, Nguyen HT, Peltekian AK, Shin AD, Song MJ, Christou AS, Hazen LA, Rivera J, Morhard RA, Bagci U, Li M, Clifton DA, Wood BJ. Digital Omicron detection using unscripted voice samples from social media. medRxiv 2022:2022. [PMID: 36172131 DOI: 10.1101/2022.09.13.22279673] [Reference Citation Analysis]
7 Tanhaeean M, Nazari N, Iranmanesh SH, Abdollahzade M. Analyzing factors contributing to COVID-19 mortality in the United States using artificial intelligence techniques. Risk Anal 2023;43:19-43. [PMID: 36464484 DOI: 10.1111/risa.14033] [Reference Citation Analysis]
8 Kuluozturk M, Kobat MA, Barua PD, Dogan S, Tuncer T, Tan RS, Ciaccio EJ, Acharya UR. DKPNet41: Directed knight pattern network-based cough sound classification model for automatic disease diagnosis. Med Eng Phys 2022;110:103870. [PMID: 35989223 DOI: 10.1016/j.medengphy.2022.103870] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
9 Atmaja BT, Zanjabila, Sasou A. On The Optimal Classifier For Affective Vocal Bursts And Stuttering Predictions Based On Pre-Trained Acoustic Embedding. 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) 2022. [DOI: 10.23919/apsipaasc55919.2022.9980310] [Reference Citation Analysis]
10 Ankur T, Kundu B, Foysal MKH, Ortiz BL, Chong JW. LSTM-Based COVID-19 Detection Method Using Coughing.. [DOI: 10.21203/rs.3.rs-2106413/v1] [Reference Citation Analysis]
11 Panah PG, Bornapour SM, Nosratabadi SM, Guerrero JM. Hesitant fuzzy for conflicting criteria in multi-objective deployment of electric vehicle charging stations. Sustainable Cities and Society 2022;85:104054. [DOI: 10.1016/j.scs.2022.104054] [Reference Citation Analysis]
12 Kumar S, Gupta SK, Kumar V, Kumar M, Chaube MK, Naik NS. Ensemble multimodal deep learning for early diagnosis and accurate classification of COVID-19. Comput Electr Eng 2022;103:108396. [PMID: 36160764 DOI: 10.1016/j.compeleceng.2022.108396] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 Consuegra-ayala JP, Gutiérrez Y, Almeida-cruz Y, Palomar M. Intelligent ensembling of auto-ML system outputs for solving classification problems. Information Sciences 2022;609:766-80. [DOI: 10.1016/j.ins.2022.07.061] [Reference Citation Analysis]
14 Wang G, Wang L, Meng Z, Su X, Jia C, Qiao X, Pan S, Chen Y, Cheng Y, Zhu M. Visual Detection of COVID-19 from Materials Aspect. Adv Fiber Mater 2022;4:1304-33. [PMID: 35966612 DOI: 10.1007/s42765-022-00179-y] [Reference Citation Analysis]