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Cited by in CrossRef
For: Dalal S, Onyema EM, Malik A. Hybrid XGBoost model with hyperparameter tuning for prediction of liver disease with better accuracy. World J Gastroenterol 2022; 28(46): 6551-6563 [PMID: 36569269 DOI: 10.3748/wjg.v28.i46.6551]
URL: https://www.wjgnet.com/1007-9327/full/v28/i46/6551.htm
Number Citing Articles
1
Surjeet Dalal, Bijeta Seth, Magdalena Radulescu. Digitalization, Sustainable Development, and Industry 5.02023; : 267 doi: 10.1108/978-1-83753-190-520231014
2
Pinamala Sruthi, R. Suhasini, V. Narasimha, S. Rao Chintalapudi, D. T. V. Dharmajee Rao, P. Mounika. Cybernetics, Human Cognition, and Machine Learning in Communicative ApplicationsCognitive Science and Technology 2025; : 285 doi: 10.1007/978-981-97-8533-9_18
3
Devansh Gahlawat, Shilpa Suhag, Uma Rani, Sarika Madavi. Hybrid deep learning model for IT-OT integration in Industry 4.02023 Second International Conference On Smart Technologies For Smart Nation (SmartTechCon) 2023; : 1025 doi: 10.1109/SmartTechCon57526.2023.10391501
4
Improved Machine leaning algorithms for sentiment analysis2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) 2023; : 475 doi: 10.1109/CISES58720.2023.10197648
5
Monali Ramteke, Shital Raut. Enhancing Disease Diagnosis: Leveraging Machine Learning Algorithms for Healthcare Data AnalysisIETE Journal of Research 2025; 71(2): 688 doi: 10.1080/03772063.2024.2434572
6
Yagyanath Rimal, Siddhartha Paudel, Navneet Sharma, Abeer Alsadoon. Machine learning model matters its accuracy: a comparative study of ensemble learning and AutoML using heart disease predictionMultimedia Tools and Applications 2023; 83(12): 35025 doi: 10.1007/s11042-023-16380-z
7
Srinivas Islavath, C. Rohith Bhat. Uniform resource locator phishing detection using novel extreme gradient boosting algorithm in comparison with term frequency-inverse document frequency +N gram to improve accuracyINTERNATIONAL CONFERENCE ON APPLICATION OF ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SOURCES AND ENVIRONMENTAL SUSTAINABILITY 2025; 3252: 020057 doi: 10.1063/5.0258817
8
Greeting Gesture Analysis Using Boosting Algorithms and SHAP2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS) 2024; : 1 doi: 10.1109/SCISISIS61014.2024.10759915
9
Huseyin Cagan Kilinc, Bulent Haznedar, Furkan Ozkan, Okan Mert Katipoğlu. An evolutionary hybrid method based on particle swarm optimization algorithm and extreme gradient boosting for short-term streamflow forecastingActa Geophysica 2024; 72(5): 3661 doi: 10.1007/s11600-024-01307-5
10
Erapaneni Gayatri, S. L. Aarthy. Classification of skin cancer using deep batch-normalized elu alexnet with fractional sparrow ladybug optimizationMultimedia Tools and Applications 2023; 83(14): 42319 doi: 10.1007/s11042-023-16999-y
11
Hossam S. El-Beltagi, Marwa Rageb, Mahmoud M. El-Saber, Ragab A. El-Masry, Khaled M.A. Ramadan, Mahmoud Kandeel, Ahlam Saleh Alhajri, Ali Osman. Green synthesis, characterization, and hepatoprotective effect of zinc oxide nanoparticles from Moringa oleifera leaves in CCl4-treated albino ratsHeliyon 2024; 10(9): e30627 doi: 10.1016/j.heliyon.2024.e30627
12
Prasannavenkatesan Theerthagiri. Liver disease classification using histogram-based gradient boosting classification tree with feature selection algorithmBiomedical Signal Processing and Control 2025; 100: 107102 doi: 10.1016/j.bspc.2024.107102
13
Surjeet Dalal, Bijeta Seth, Magdalena Radulescu, Teodor Florin Cilan, Luminita Serbanescu. Optimized Deep Learning with Learning without Forgetting (LwF) for Weather Classification for Sustainable Transportation and Traffic SafetySustainability 2023; 15(7): 6070 doi: 10.3390/su15076070
14
Yuk Ming Tang, Ka Yin Chau, Yui-yip Lau, Zehang Zheng. Data-Intensive Inventory Forecasting with Artificial Intelligence Models for Cross-Border E-Commerce Service AutomationApplied Sciences 2023; 13(5): 3051 doi: 10.3390/app13053051
15
Femilda Josephin Joseph Shobana Bai, R. Anita Jasmine. Decision-Making Models2024; : 523 doi: 10.1016/B978-0-443-16147-6.00015-3
16
T. Haritha, A. V. Santhosh Babu. Early-stage stroke prediction based on Parkinson and wrinkles using deep learningNeural Computing and Applications 2024; 36(30): 18781 doi: 10.1007/s00521-024-10189-z
17
Touhid Imam, Jahirul Islam, Sharmin Sultana, Md Salah Uddin, Mohammad Shihab Uddin, Bushra Uddin. ML-Driven Solutions for Chronic Liver Disease: Predictive Models and Prevention Strategies2024 IEEE International Conference on Computing (ICOCO) 2024; : 261 doi: 10.1109/ICOCO62848.2024.10928240
18
Efficient Machine leaning algorithms for sentiment analysis in Car rental sevice2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) 2023; : 475 doi: 10.1109/CISES58720.2023.10183424
19
Zheyu Du, Ling Yang, Hongliang He, Xiaofeng Wu, Xiaolong Qi, Yudong Zhang. Artificial intelligence for the noninvasive diagnosis of clinically significant portal hypertensionEngMedicine 2025; 2(2): 100069 doi: 10.1016/j.engmed.2025.100069
20
Surjeet Dalal, Umesh Kumar Lilhore, Poongodi Manoharan, Uma Rani, Fadl Dahan, Fahima Hajjej, Ismail Keshta, Ashish Sharma, Sarita Simaiya, Kaamran Raahemifar. An Efficient Brain Tumor Segmentation Method Based on Adaptive Moving Self-Organizing Map and Fuzzy K-Mean ClusteringSensors 2023; 23(18): 7816 doi: 10.3390/s23187816
21
Chengli Wen, Xu Zhang, Yong Li, Wanmeng Xiao, Qinxue Hu, Xianying Lei, Tao Xu, Sicheng Liang, Xiaolan Gao, Chao Zhang, Zehui Yu, Muhan Lü, Nattapol Aunsri. An interpretable machine learning model for predicting 28-day mortality in patients with sepsis-associated liver injuryPLOS ONE 2024; 19(5): e0303469 doi: 10.1371/journal.pone.0303469
22
D. Antony Pradeesh, Y. Syamala, P. Priya, Madhavi Sripathi, Srilakshmi Kaza, Rohith Bala Jaswanth B. Advanced Interoperable Framework for Real-Time Predictive Analysis Leveraging Machine Learning and IoT in Smart Health Monitoring Systems2023 International Conference on Electrical, Computer and Energy Technologies (ICECET) 2023; : 1 doi: 10.1109/ICECET58911.2023.10389275
23
Kunal Jha, Hasim Ali, Akshat Sharma, Neda Fatima. Bridging Healthcare Gaps: Sustainable Liver Disease Diagnosis Using Machine Learning in Resource-Limited Regions2025 2nd International Conference on Computational Intelligence, Communication Technology and Networking (CICTN) 2025; : 618 doi: 10.1109/CICTN64563.2025.10932560
24
Chenjun Wu, Toshihiro Omori, Takuji Ishikawa. Drag force on a microrobot propelled through bloodCommunications Physics 2024; 7(1) doi: 10.1038/s42005-024-01724-4
25
Efficient Machine Leaning Algorithms for Sentiment Analysis In Car Rental Service2023 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES) 2023; : 452 doi: 10.1109/CISES58720.2023.10183435
26
Xiaoshuai Zhang, Chuanping Tang, Shuohuan Wang, Wei Liu, Wangxuan Yang, Di Wang, Qinghuan Wang, Fang Tang. A stacking ensemble model for predicting the occurrence of carotid atherosclerosisFrontiers in Endocrinology 2024; 15 doi: 10.3389/fendo.2024.1390352
27
Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik. Predicting Chronic Liver Disease Using Boosting Technique2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI) 2023; : 1 doi: 10.1109/ICAIIHI57871.2023.10489026
28
Trends in Mechatronics SystemsEmerging Trends in Mechatronics 2024; : 73 doi: 10.1007/978-981-97-9108-8_5
29
Ayça Nur Şahin Demirel, Taner Erik. Determination of the effect of climate change on small cattle milk yield in Iğdır province via machine learningHarran Tarım ve Gıda Bilimleri Dergisi 2024; 28(3): 374 doi: 10.29050/harranziraat.1464601
30
Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik. A comparative analysis of boosting algorithms for chronic liver disease predictionHealthcare Analytics 2024; 5: 100313 doi: 10.1016/j.health.2024.100313
31
Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Zhongming Zhao. Improved liver disease prediction from clinical data through an evaluation of ensemble learning approachesBMC Medical Informatics and Decision Making 2024; 24(1) doi: 10.1186/s12911-024-02550-y