166 related articles for article (PubMed ID: 35901023)
1. An empirical evaluation of sampling methods for the classification of imbalanced data.
Kim M; Hwang KB
PLoS One; 2022; 17(7):e0271260. PubMed ID: 35901023
[TBL] [Abstract][Full Text] [Related]
2. Establishment of noninvasive diabetes risk prediction model based on tongue features and machine learning techniques.
Li J; Chen Q; Hu X; Yuan P; Cui L; Tu L; Cui J; Huang J; Jiang T; Ma X; Yao X; Zhou C; Lu H; Xu J
Int J Med Inform; 2021 May; 149():104429. PubMed ID: 33647600
[TBL] [Abstract][Full Text] [Related]
3. Conversion of adverse data corpus to shrewd output using sampling metrics.
Ashraf S; Saleem S; Ahmed T; Aslam Z; Muhammad D
Vis Comput Ind Biomed Art; 2020 Aug; 3(1):19. PubMed ID: 32779031
[TBL] [Abstract][Full Text] [Related]
4. The performance of VCS(volume, conductivity, light scatter) parameters in distinguishing latent tuberculosis and active tuberculosis by using machine learning algorithm.
Chen L; Yuan L; Sun T; Liu R; Huang Q; Deng S
BMC Infect Dis; 2023 Dec; 23(1):881. PubMed ID: 38104064
[TBL] [Abstract][Full Text] [Related]
5. A soft voting ensemble learning approach for credit card fraud detection.
Azim Mim M; Majadi N; Mazumder P
Heliyon; 2024 Feb; 10(3):e25466. PubMed ID: 38333818
[TBL] [Abstract][Full Text] [Related]
6. Analysis of sampling techniques for imbalanced data: An n = 648 ADNI study.
Dubey R; Zhou J; Wang Y; Thompson PM; Ye J;
Neuroimage; 2014 Feb; 87():220-41. PubMed ID: 24176869
[TBL] [Abstract][Full Text] [Related]
7. Classifying adverse drug reactions from imbalanced twitter data.
Dai HJ; Wang CK
Int J Med Inform; 2019 Sep; 129():122-132. PubMed ID: 31445246
[TBL] [Abstract][Full Text] [Related]
8. Using machine learning to predict opioid misuse among U.S. adolescents.
Han DH; Lee S; Seo DC
Prev Med; 2020 Jan; 130():105886. PubMed ID: 31705938
[TBL] [Abstract][Full Text] [Related]
9. Comparison of Resampling Techniques for Imbalanced Datasets in Machine Learning: Application to Epileptogenic Zone Localization From Interictal Intracranial EEG Recordings in Patients With Focal Epilepsy.
Varotto G; Susi G; Tassi L; Gozzo F; Franceschetti S; Panzica F
Front Neuroinform; 2021; 15():715421. PubMed ID: 34867255
[No Abstract] [Full Text] [Related]
10. Assessing and mitigating the effects of class imbalance in machine learning with application to X-ray imaging.
Qu W; Balki I; Mendez M; Valen J; Levman J; Tyrrell PN
Int J Comput Assist Radiol Surg; 2020 Dec; 15(12):2041-2048. PubMed ID: 32965624
[TBL] [Abstract][Full Text] [Related]
11. Assessing the predictive ability of the Suicide Crisis Inventory for near-term suicidal behavior using machine learning approaches.
Parghi N; Chennapragada L; Barzilay S; Newkirk S; Ahmedani B; Lok B; Galynker I
Int J Methods Psychiatr Res; 2021 Mar; 30(1):e1863. PubMed ID: 33166430
[TBL] [Abstract][Full Text] [Related]
12. Improved support vector machine classification for imbalanced medical datasets by novel hybrid sampling combining modified mega-trend-diffusion and bagging extreme learning machine model.
Lin LS; Kao CH; Li YJ; Chen HH; Chen HY
Math Biosci Eng; 2023 Sep; 20(10):17672-17701. PubMed ID: 38052532
[TBL] [Abstract][Full Text] [Related]
13. Meta-EHR: A meta-learning approach for electronic health records with a high imbalanced ratio and missing rate.
Chang HH; Hsu TC; Hsieh YH; Lin C
Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083168
[TBL] [Abstract][Full Text] [Related]
14. A machine learning approach using conditional normalizing flow to address extreme class imbalance problems in personal health records.
Kim Y; Choi W; Choi W; Ko G; Han S; Kim HC; Kim D; Lee DG; Shin DW; Lee Y
BioData Min; 2024 May; 17(1):14. PubMed ID: 38796471
[TBL] [Abstract][Full Text] [Related]
15. Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data.
Thölke P; Mantilla-Ramos YJ; Abdelhedi H; Maschke C; Dehgan A; Harel Y; Kemtur A; Mekki Berrada L; Sahraoui M; Young T; Bellemare Pépin A; El Khantour C; Landry M; Pascarella A; Hadid V; Combrisson E; O'Byrne J; Jerbi K
Neuroimage; 2023 Aug; 277():120253. PubMed ID: 37385392
[TBL] [Abstract][Full Text] [Related]
16. Effect of machine learning re-sampling techniques for imbalanced datasets in
Xie C; Du R; Ho JW; Pang HH; Chiu KW; Lee EY; Vardhanabhuti V
Eur J Nucl Med Mol Imaging; 2020 Nov; 47(12):2826-2835. PubMed ID: 32253486
[TBL] [Abstract][Full Text] [Related]
17. Social Reminiscence in Older Adults' Everyday Conversations: Automated Detection Using Natural Language Processing and Machine Learning.
Ferrario A; Demiray B; Yordanova K; Luo M; Martin M
J Med Internet Res; 2020 Sep; 22(9):e19133. PubMed ID: 32866108
[TBL] [Abstract][Full Text] [Related]
18. Imbalanced learning: Improving classification of diabetic neuropathy from magnetic resonance imaging.
Teh K; Armitage P; Tesfaye S; Selvarajah D; Wilkinson ID
PLoS One; 2020; 15(12):e0243907. PubMed ID: 33320890
[TBL] [Abstract][Full Text] [Related]
19. A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms.
Carrington AM; Fieguth PW; Qazi H; Holzinger A; Chen HH; Mayr F; Manuel DG
BMC Med Inform Decis Mak; 2020 Jan; 20(1):4. PubMed ID: 31906931
[TBL] [Abstract][Full Text] [Related]
20. Machine learning algorithms, bull genetic information, and imbalanced datasets used in abortion incidence prediction models for Iranian Holstein dairy cattle.
Keshavarzi H; Sadeghi-Sefidmazgi A; Mirzaei A; Ravanifard R
Prev Vet Med; 2020 Feb; 175():104869. PubMed ID: 31896505
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
