1279 related articles for article (PubMed ID: 35632184)
1. Machine Learning-Based Boosted Regression Ensemble Combined with Hyperparameter Tuning for Optimal Adaptive Learning.
Isabona J; Imoize AL; Kim Y
Sensors (Basel); 2022 May; 22(10):. PubMed ID: 35632184
[TBL] [Abstract][Full Text] [Related]
2. Evaluating the performance of machine learning methods and variable selection methods for predicting difficult-to-measure traits in Holstein dairy cattle using milk infrared spectral data.
Mota LFM; Pegolo S; Baba T; Peñagaricano F; Morota G; Bittante G; Cecchinato A
J Dairy Sci; 2021 Jul; 104(7):8107-8121. PubMed ID: 33865589
[TBL] [Abstract][Full Text] [Related]
3. HGSORF: Henry Gas Solubility Optimization-based Random Forest for C-Section prediction and XAI-based cause analysis.
Islam MS; Awal MA; Laboni JN; Pinki FT; Karmokar S; Mumenin KM; Al-Ahmadi S; Rahman MA; Hossain MS; Mirjalili S
Comput Biol Med; 2022 Aug; 147():105671. PubMed ID: 35660327
[TBL] [Abstract][Full Text] [Related]
4. Predictive modeling of blood pressure during hemodialysis: a comparison of linear model, random forest, support vector regression, XGBoost, LASSO regression and ensemble method.
Huang JC; Tsai YC; Wu PY; Lien YH; Chien CY; Kuo CF; Hung JF; Chen SC; Kuo CH
Comput Methods Programs Biomed; 2020 Oct; 195():105536. PubMed ID: 32485511
[TBL] [Abstract][Full Text] [Related]
5. Optimizing Machine Learning Algorithms for Landslide Susceptibility Mapping along the Karakoram Highway, Gilgit Baltistan, Pakistan: A Comparative Study of Baseline, Bayesian, and Metaheuristic Hyperparameter Optimization Techniques.
Abbas F; Zhang F; Ismail M; Khan G; Iqbal J; Alrefaei AF; Albeshr MF
Sensors (Basel); 2023 Aug; 23(15):. PubMed ID: 37571627
[TBL] [Abstract][Full Text] [Related]
6. Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers.
Kawakami E; Tabata J; Yanaihara N; Ishikawa T; Koseki K; Iida Y; Saito M; Komazaki H; Shapiro JS; Goto C; Akiyama Y; Saito R; Saito M; Takano H; Yamada K; Okamoto A
Clin Cancer Res; 2019 May; 25(10):3006-3015. PubMed ID: 30979733
[TBL] [Abstract][Full Text] [Related]
7. Bayesian Optimization with Support Vector Machine Model for Parkinson Disease Classification.
Elshewey AM; Shams MY; El-Rashidy N; Elhady AM; Shohieb SM; Tarek Z
Sensors (Basel); 2023 Feb; 23(4):. PubMed ID: 36850682
[TBL] [Abstract][Full Text] [Related]
8. Development of a Prediction Model for Demolition Waste Generation Using a Random Forest Algorithm Based on Small DataSets.
Cha GW; Moon HJ; Kim YM; Hong WH; Hwang JH; Park WJ; Kim YC
Int J Environ Res Public Health; 2020 Sep; 17(19):. PubMed ID: 32987874
[TBL] [Abstract][Full Text] [Related]
9. An optimized XGBoost-based machine learning method for predicting wave run-up on a sloping beach.
Tarwidi D; Pudjaprasetya SR; Adytia D; Apri M
MethodsX; 2023; 10():102119. PubMed ID: 37007622
[TBL] [Abstract][Full Text] [Related]
10. Occupational Injury Risk Mitigation: Machine Learning Approach and Feature Optimization for Smart Workplace Surveillance.
Khairuddin MZF; Lu Hui P; Hasikin K; Abd Razak NA; Lai KW; Mohd Saudi AS; Ibrahim SS
Int J Environ Res Public Health; 2022 Oct; 19(21):. PubMed ID: 36360843
[TBL] [Abstract][Full Text] [Related]
11. Classification of imbalanced data using machine learning algorithms to predict the risk of renal graft failures in Ethiopia.
Mulugeta G; Zewotir T; Tegegne AS; Juhar LH; Muleta MB
BMC Med Inform Decis Mak; 2023 May; 23(1):98. PubMed ID: 37217892
[TBL] [Abstract][Full Text] [Related]
12. Predicting the sorption efficiency of heavy metal based on the biochar characteristics, metal sources, and environmental conditions using various novel hybrid machine learning models.
Ke B; Nguyen H; Bui XN; Bui HB; Choi Y; Zhou J; Moayedi H; Costache R; Nguyen-Trang T
Chemosphere; 2021 Aug; 276():130204. PubMed ID: 34088091
[TBL] [Abstract][Full Text] [Related]
13. Performance Evaluation of Regression Models for the Prediction of the COVID-19 Reproduction Rate.
Kaliappan J; Srinivasan K; Mian Qaisar S; Sundararajan K; Chang CY; C S
Front Public Health; 2021; 9():729795. PubMed ID: 34595149
[TBL] [Abstract][Full Text] [Related]
14. Machine learning random forest for predicting oncosomatic variant NGS analysis.
Pellegrino E; Jacques C; Beaufils N; Nanni I; Carlioz A; Metellus P; Ouafik L
Sci Rep; 2021 Nov; 11(1):21820. PubMed ID: 34750410
[TBL] [Abstract][Full Text] [Related]
15. Ensemble effort estimation with metaheuristic hyperparameters and weight optimization for achieving accuracy.
Yasmin A; Haider Butt W; Daud A
PLoS One; 2024; 19(4):e0300296. PubMed ID: 38573895
[TBL] [Abstract][Full Text] [Related]
16. Optimizing PGRs for in vitro shoot proliferation of pomegranate with bayesian-tuned ensemble stacking regression and NSGA-II: a comparative evaluation of machine learning models.
Zarbakhsh S; Shahsavar AR; Soltani M
Plant Methods; 2024 May; 20(1):82. PubMed ID: 38822411
[TBL] [Abstract][Full Text] [Related]
17. Comparison of Random Forest and Gradient Boosting Machine Models for Predicting Demolition Waste Based on Small Datasets and Categorical Variables.
Cha GW; Moon HJ; Kim YC
Int J Environ Res Public Health; 2021 Aug; 18(16):. PubMed ID: 34444277
[TBL] [Abstract][Full Text] [Related]
18. Identifying tuberculous pleural effusion using artificial intelligence machine learning algorithms.
Ren Z; Hu Y; Xu L
Respir Res; 2019 Oct; 20(1):220. PubMed ID: 31619240
[TBL] [Abstract][Full Text] [Related]
19. Robust clustering-based hybrid technique enabling reliable reservoir water quality prediction with uncertainty quantification and spatial analysis.
Fooladi M; Nikoo MR; Mirghafari R; Madramootoo CA; Al-Rawas G; Nazari R
J Environ Manage; 2024 Jun; 362():121259. PubMed ID: 38830281
[TBL] [Abstract][Full Text] [Related]
20. Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.
Awad A; Bader-El-Den M; McNicholas J; Briggs J
Int J Med Inform; 2017 Dec; 108():185-195. PubMed ID: 29132626
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
