Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 177, P. 108592 - 108592
Published: May 16, 2024
Language: Английский
Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 177, P. 108592 - 108592
Published: May 16, 2024
Language: Английский
Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135123 - 135123
Published: Feb. 1, 2025
Language: Английский
Citations
2Biomedical Signal Processing and Control, Journal Year: 2024, Volume and Issue: 94, P. 106246 - 106246
Published: March 30, 2024
Language: Английский
Citations
15Advances in respiratory medicine, Journal Year: 2024, Volume and Issue: 92(5), P. 395 - 420
Published: Oct. 17, 2024
The global healthcare system faces challenges in diagnosing and managing lung colon cancers, which are significant health burdens. Traditional diagnostic methods inefficient prone to errors, while data privacy security concerns persist.
Language: Английский
Citations
10Transportation Research Part E Logistics and Transportation Review, Journal Year: 2024, Volume and Issue: 192, P. 103770 - 103770
Published: Sept. 20, 2024
Language: Английский
Citations
9Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 177, P. 108646 - 108646
Published: May 24, 2024
Language: Английский
Citations
6JMIRx Med, Journal Year: 2024, Volume and Issue: 5, P. e56993 - e56993
Published: April 24, 2024
Noncommunicable diseases continue to pose a substantial health challenge globally, with hyperglycemia serving as prominent indicator of diabetes.
Language: Английский
Citations
4Nutrition and Diabetes, Journal Year: 2024, Volume and Issue: 14(1)
Published: Aug. 14, 2024
Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose challenge to accurate diabetes prediction. This imbalance often results in models performing poorly predicting minority classes, overall diagnostic performance. To address this issue, study employs combination of Synthetic Minority Over-sampling Technique (SMOTE) Random Under-Sampling (RUS) data balancing uses Optuna hyperparameter optimization machine learning models. approach aims fill the gap current research concerning model optimization, thereby improving prediction accuracy computational efficiency. First, SMOTE RUS methods process dataset, distribution. Then, is utilized optimize hyperparameters LightGBM enhance its During experiment, effectiveness proposed evaluated by comparing training dataset before after balancing. The experimental show that enhanced LightGBM-Optuna improves from 97.07% 97.11%, precision 97.17% 98.99%. time required single search only 2.5 seconds. These demonstrate superiority method handling optimizing indicates combining algorithms with can effectively models, especially dealing
Language: Английский
Citations
4Egyptian Informatics Journal, Journal Year: 2025, Volume and Issue: 29, P. 100606 - 100606
Published: Jan. 8, 2025
Language: Английский
Citations
0Swarm and Evolutionary Computation, Journal Year: 2025, Volume and Issue: 94, P. 101864 - 101864
Published: Feb. 9, 2025
Language: Английский
Citations
0International Journal of Fuzzy Systems, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 19, 2025
Language: Английский
Citations
0