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For: Ghiasi MM, Zendehboudi S. Application of decision tree-based ensemble learning in the classification of breast cancer. Comput Biol Med 2021;128:104089. [PMID: 33338982 DOI: 10.1016/j.compbiomed.2020.104089] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
Number Citing Articles
1 Moslehi S, Rabiei N, Soltanian AR, Mamani M. Application of machine learning models based on decision trees in classifying the factors affecting mortality of COVID-19 patients in Hamadan, Iran. BMC Med Inform Decis Mak 2022;22. [DOI: 10.1186/s12911-022-01939-x] [Reference Citation Analysis]
2 Ileberi E, Sun Y, Wang Z. A machine learning based credit card fraud detection using the GA algorithm for feature selection. J Big Data 2022;9. [DOI: 10.1186/s40537-022-00573-8] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Ekmekcioğlu Ö, Koc K. Explainable step-wise binary classification for the susceptibility assessment of geo-hydrological hazards. CATENA 2022;216:106379. [DOI: 10.1016/j.catena.2022.106379] [Reference Citation Analysis]
4 Zhang F, Zhang Y, Zhu X, Chen X, Du H, Zhang X. PregGAN: A prognosis prediction model for breast cancer based on conditional generative adversarial networks. Comput Methods Programs Biomed 2022;224:107026. [PMID: 35872384 DOI: 10.1016/j.cmpb.2022.107026] [Reference Citation Analysis]
5 Pei Q, Luo Y, Chen Y, Li J, Xie D, Ye T. Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis. Clin Chem Lab Med 2022. [PMID: 35771735 DOI: 10.1515/cclm-2022-0291] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Hussain SM, Buongiorno D, Altini N, Berloco F, Prencipe B, Moschetta M, Bevilacqua V, Brunetti A. Shape-Based Breast Lesion Classification Using Digital Tomosynthesis Images: The Role of Explainable Artificial Intelligence. Applied Sciences 2022;12:6230. [DOI: 10.3390/app12126230] [Reference Citation Analysis]
7 Zhang Y, Zhu G, Li K, Li F, Huang L, Duan M, Zhou F. HLAB: learning the BiLSTM features from the ProtBert-encoded proteins for the class I HLA-peptide binding prediction. Brief Bioinform 2022:bbac173. [PMID: 35514183 DOI: 10.1093/bib/bbac173] [Reference Citation Analysis]
8 Bacha S, Ben Abdellafou K, Aljuhani A, Taouali O, Liouane N. Early detection of digital mammogram using kernel extreme learning machine. Concurrency and Computation 2022;34. [DOI: 10.1002/cpe.6971] [Reference Citation Analysis]
9 Zhang K, Qian Z, Yang Y, Chen M, Zhong T, Zhu R, Lv G, Yan J. Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis. Sustainable Cities and Society 2022;78:103598. [DOI: 10.1016/j.scs.2021.103598] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Adhikary S, Ghosh A. Dynamic time warping approach for optimized locomotor impairment detection using biomedical signal processing. Biomedical Signal Processing and Control 2022;72:103321. [DOI: 10.1016/j.bspc.2021.103321] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
11 Zare M, Zendehboudi S, Abdi MA. Deterministic tools to estimate induction time for methane hydrate formation in the presence of Luvicap 55 W solutions. Journal of Molecular Liquids 2022;348:118374. [DOI: 10.1016/j.molliq.2021.118374] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Jiang F, Zhu Q, Tian T. Breast Cancer Detection Based on Modified Harris Hawks Optimization and Extreme Learning Machine Embedded with Feature Weighting. Neural Process Lett. [DOI: 10.1007/s11063-021-10700-w] [Reference Citation Analysis]
13 Varzaneh ZA, Orooji A, Erfannia L, Shanbehzadeh M. A new COVID-19 intubation prediction strategy using an intelligent feature selection and K-NN method. Inform Med Unlocked 2022;28:100825. [PMID: 34977330 DOI: 10.1016/j.imu.2021.100825] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
14 Wang J. . MBE 2022;19:10407-23. [DOI: 10.3934/mbe.2022487] [Reference Citation Analysis]
15 Huang Z, Chen D. A Breast Cancer Diagnosis Method Based on VIM Feature Selection and Hierarchical Clustering Random Forest Algorithm. IEEE Access 2022;10:3284-93. [DOI: 10.1109/access.2021.3139595] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
16 Kovacs D, Msanga DR, Mshana SE, Bilal M, Oravcova K, Matthews L. Developing practical clinical tools for predicting neonatal mortality at a neonatal intensive care unit in Tanzania. BMC Pediatr 2021;21:537. [PMID: 34852794 DOI: 10.1186/s12887-021-03012-4] [Reference Citation Analysis]
17 Koc K, Ekmekcioğlu Ö, Gurgun AP. Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers. Automation in Construction 2021;131:103896. [DOI: 10.1016/j.autcon.2021.103896] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
18 Makond B, Wang KJ, Wang KM. Benchmarking prognosis methods for survivability - A case study for patients with contingent primary cancers. Comput Biol Med 2021;138:104888. [PMID: 34610552 DOI: 10.1016/j.compbiomed.2021.104888] [Reference Citation Analysis]
19 Tang L, Liu G. The novel approach of temporal dependency complexity analysis of heart rate variability in obstructive sleep apnea. Comput Biol Med 2021;135:104632. [PMID: 34265554 DOI: 10.1016/j.compbiomed.2021.104632] [Reference Citation Analysis]
20 Xiong Y, Ye M, Wu C. Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble. Comput Math Methods Med 2021;2021:5556992. [PMID: 33986823 DOI: 10.1155/2021/5556992] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]