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Cited by in CrossRef
For: Alkhawaldeh IM, Albalkhi I, Naswhan AJ. Challenges and limitations of synthetic minority oversampling techniques in machine learning. World J Methodol 2023; 13(5): 373-378 [PMID: 38229946 DOI: 10.5662/wjm.v13.i5.373]
URL: https://www.wjgnet.com/2222-0682/full/v13/i5/373.htm
Number Citing Articles
1
Zahra Mohammadi-Pirouz, Karimollah Hajian-Tilaki, Mahmoud Sadeghi Haddat-Zavareh, Abazar Amoozadeh, Shabnam Bahrami. Development of decision tree classification algorithms in predicting mortality of COVID-19 patientsInternational Journal of Emergency Medicine 2024; 17(1) doi: 10.1186/s12245-024-00681-7
2
Siyu Chen, Jinwen Zheng, Jinying Li. The Impact of Sample Size after Sampling on the Accuracy of Machine Learning Models2024 International Conference on Computers, Information Processing and Advanced Education (CIPAE) 2024; : 61 doi: 10.1109/CIPAE64326.2024.00017
3
Andrea Heaney, Emma Murphy, Eugene Hickey. Pervasive Computing Technologies for HealthcareLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025; 611: 179 doi: 10.1007/978-3-031-85572-6_11
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Aditya Bhattacharya, Simone Stumpf, Katrien Verbert. Representation Debiasing of Generated Data Involving Domain ExpertsAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization 2024; : 516 doi: 10.1145/3631700.3664910
5
Aysha Akther, Kazi Masudul Alam, Rameswar Debnath. Automatic detection of manipulated Bangla news: A new knowledge-driven approachNatural Language Processing Journal 2025; 11: 100155 doi: 10.1016/j.nlp.2025.100155
6
Lauren McBride, Varsha D. Badal, Philip D. Harvey, Amy Pinkham, Ankit Aich, Natalie Parde, Colin Depp. Evaluating natural language processing derived linguistic features associated with current suicidal ideation, past attempts, and future suicidal behaviorJournal of Psychiatric Research 2025; 187: 25 doi: 10.1016/j.jpsychires.2025.05.004
7
Siyi Yuan, Song Xu, Xiao Lu, Xiangyu Chen, Yao Wang, Renyi Bao, Yunbo Sun, Xiongjian Xiao, Longxiang Su, Yun Long, Linfeng Li, Huaiwu He. A privacy-preserving platform oriented medical healthcare and its application in identifying patients with candidemiaScientific Reports 2024; 14(1) doi: 10.1038/s41598-024-66596-8
8
Kaliprasanna Swain, Tan Kuan Tak, Kamal Upreti, Pravin R Kshirsagar, Sivaneasan Bala Krishnan, Ramesh Chandra Poonia, Sumya Ranjan Nayak, Mihir Narayan Mohanty. Enhancing Stroke Prediction Using LightGBM With SMOTE-ENN and Fine-Tuning: A Comprehensive AnalysisCureus Journal of Computer Science 2024;  doi: 10.7759/s44389-024-02268-y
9
Muhammad Kamran, Muhammad Maaz Rehan, Wasif Nisar, Muhammad Waqas Rehan. ARCADE—Adversarially Robust Cost-Sensitive Anomaly Detection in Blockchain Using Explainable Artificial IntelligenceElectronics 2025; 14(8): 1648 doi: 10.3390/electronics14081648
10
Aditya Bhattacharya, Simone Stumpf, Robin De Croon, Katrien Verbert. Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI SystemsProceedings of the 2025 CHI Conference on Human Factors in Computing Systems 2025; : 1 doi: 10.1145/3706598.3713497
11
Thawirasm Jungrungrueang, Sawrawit Chairat, Kasidach Rasitanon, Praopim Limsakul, Krit Charupanit. Translational approach for dementia subtype classification using convolutional neural network based on EEG connectome dynamicsScientific Reports 2025; 15(1) doi: 10.1038/s41598-025-02018-7
12
Hyukjun Lee, Ji Won Han, Seung Wan Suh, Hee Won Yang, Dae Jong Oh, Eunji Lim, Jin Shin, Bong Jo Kim, Dong Woo Lee, Jeong Lan Kim, Jin Hyeong Jhoo, Joon Hyuk Park, Jung Jae Lee, Kyung Phil Kwak, Seok Bum Lee, Seok Woo Moon, Seung-Ho Ryu, Shin Gyeom Kim, Ki Woong Kim. A sleep-based risk model for predicting dementia: Development and validation in a Korean cohortJournal of Alzheimer’s Disease 2025;  doi: 10.1177/13872877251340094
13
Lidan Liu, Bo Liu, Ming Liao, Qiuying Gan, Qianyi Huang, Yihua Yang. Identifying key predictive features for live birth rate in advanced maternal age patients undergoing single vitrified-warmed blastocyst transferReproductive Biology and Endocrinology 2024; 22(1) doi: 10.1186/s12958-024-01295-7
14
Blanca Vazquez, Nidiyare Hevia-Montiel, Jorge Perez-Gonzalez, Paulina Haro, Lei Chu. Weighted–VAE: A deep learning approach for multimodal data generation applied to experimental T. cruzi infectionPLOS ONE 2025; 20(3): e0315843 doi: 10.1371/journal.pone.0315843
15
Tajul Miftahushudur, Halil Mertkan Sahin, Bruce Grieve, Hujun Yin. A Survey of Methods for Addressing Imbalance Data Problems in Agriculture ApplicationsRemote Sensing 2025; 17(3): 454 doi: 10.3390/rs17030454
16
Damian Mikulski, Marcin Kamil Kędzior, Grzegorz Mirocha, Katarzyna Jerzmanowska-Piechota, Żaneta Witas, Łukasz Woźniak, Magdalena Pawlak, Kacper Kościelny, Michał Kośny, Paweł Robak, Aleksandra Gołos, Tadeusz Robak, Wojciech Fendler, Joanna Góra-Tybor. Predictors and Profile of Severe Infectious Complications in Multiple Myeloma Patients Treated with Daratumumab-Based Regimens: A Machine Learning Model for Pneumonia RiskCancers 2024; 16(21): 3709 doi: 10.3390/cancers16213709
17
Redet Assefa, Adane Mamuye, Marco Piangerelli. COVID-19 Severity Classification Using Hybrid Feature Extraction: Integrating Persistent Homology, Convolutional Neural Networks and Vision TransformersBig Data and Cognitive Computing 2025; 9(4): 83 doi: 10.3390/bdcc9040083
18
Sylvester Gomes, Harpreet Dhanoa, Phil Assheton, Ewan Carr, Damian Roland, Akash Deep. Predicting sepsis treatment decisions in the paediatric emergency department using machine learning: the AiSEPTRON studyBMJ Paediatrics Open 2025; 9(1): e003273 doi: 10.1136/bmjpo-2024-003273
19
Tom Velez, Zara Ibrahim, Kanayo Duru, Dante Velez, Maria Triantafyllou, Kenneth McKinley, Pasha Saif, Panagiotis Kratimenos, Andy Clark, Ioannis Koutroulis. Predicting hospital admissions, ICU utilization, and prolonged length of stay among febrile pediatric emergency department patients using incomplete and imbalanced electronic health record (EHR) data strategiesInternational Journal of Medical Informatics 2025; 200: 105905 doi: 10.1016/j.ijmedinf.2025.105905
20
Performance Analysis of Facial Expression Recognition by Using Geometry Augmentation and Random Oversampling for CNN Model2024 10th International Conference on Smart Computing and Communication (ICSCC) 2024; : 614 doi: 10.1109/ICSCC62041.2024.10690584
21
Prashanth S. Javali, Ashish Kumar, Subhajit Sarkar, R. Sree Varshini, D. Jose Mathew, Kavitha Thirumurugan. Advances in Pharmacology 2025;  doi: 10.1016/bs.apha.2025.01.017
22
Lidan Liu, Bo Liu, Huimei Wu, Qiuying Gan, Qianyi Huang, Mujun Li. Optimizing predictive features using machine learning for early miscarriage risk following single vitrified-warmed blastocyst transferFrontiers in Endocrinology 2025; 16 doi: 10.3389/fendo.2025.1557667
23
Sonali Lunawat, Jyoti Rao, Pramod Patil. ASBO-MAT-BiLSTM: Social Media Network Anomaly Detection Using Optimized Multihead Attention Transformer based Model2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) 2025; : 2209 doi: 10.1109/IDCIOT64235.2025.10915016
24
Penglu Yang, Bin Yang, Sameena Naaz. Development and validation of predictive models for diabetic retinopathy using machine learningPLOS ONE 2025; 20(2): e0318226 doi: 10.1371/journal.pone.0318226
25
Manuel Sigle, Wenke Faller, Diana Heurich, Monika Zdanyte, Robert Wunderlich, Meinrad Gawaz, Karin Anne Lydia Müller, Andreas Goldschmied. Machine learning predicts emergency physician specialties from treatment strategies for patients suspected of myocardial infarctionInternational Journal of Cardiology 2024; 413: 132332 doi: 10.1016/j.ijcard.2024.132332
26
Michael Peng, Elisheva R. Stern, Hanwen Hu. Forecasting China bond default with severe class-imbalanced data: A simple learning model with causal inferenceEconomic Modelling 2025; 144: 106985 doi: 10.1016/j.econmod.2024.106985
27
Muhammad Nazim Razali, Nureize Arbaiy, Pei-Chun Lin, Syafikrudin Ismail. Optimizing Multiclass Classification Using Convolutional Neural Networks with Class Weights and Early Stopping for Imbalanced DatasetsElectronics 2025; 14(4): 705 doi: 10.3390/electronics14040705
28
Jun Wan, Jia Zhou. Use machine learning to predict bone metastasis of esophageal cancer: A population-based studyDIGITAL HEALTH 2025; 11 doi: 10.1177/20552076251325960