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Cited by in CrossRef
For: Charilaou P, Battat R. Machine learning models and over-fitting considerations. World J Gastroenterol 2022; 28(5): 605-607 [PMID: 35316964 DOI: 10.3748/wjg.v28.i5.605]
URL: https://www.wjgnet.com/1007-9327/full/v28/i5/605.htm
Number Citing Articles
1
Ruth Salim, Simon Husby, Christian Winther Eskelund, David W. Scott, Harald Holte, Arne Kolstad, Riikka Räty, Sara Ek, Mats Jerkeman, Christian Geisler, Lasse Sommer Kristensen, Mette Dahl, Kirsten Grønbæk. Exploring new prognostic biomarkers in Mantle Cell Lymphoma: a comparison of the circSCORE and the MCL35 scoreLeukemia & Lymphoma 2023; 64(8): 1414 doi: 10.1080/10428194.2023.2216819
2
Eric McMullen, Dharmayu Desai, Yousif Al-Naser, Jeff Donovan. Applications of Machine Learning on Alopecia Areata: A Systematic ReviewJournal of Cutaneous Medicine and Surgery 2024;  doi: 10.1177/12034754241238503
3
Yanan Gu, Ruyi Cao, Dong Wang, Bibo Lu. CMP-UNet: A Retinal Vessel Segmentation Network Based on Multi-Scale Feature FusionElectronics 2023; 12(23): 4743 doi: 10.3390/electronics12234743
4
Milad Hosseinpour, Mohammad Javad Shojaei, Mohsen Salimi, Majid Amidpour. Machine learning in absorption-based post-combustion carbon capture systems: A state-of-the-art reviewFuel 2023; 353: 129265 doi: 10.1016/j.fuel.2023.129265
5
Marc Emmenegger, Vishalini Emmenegger, Srikanth Mairpady Shambat, Thomas C. Scheier, Alejandro Gomez-Mejia, Chun-Chi Chang, Pedro D. Wendel-Garcia, Philipp K. Buehler, Thomas Buettner, Dirk Roggenbuck, Silvio D. Brugger, Katrin B.M. Frauenknecht. Antiphospholipid antibodies are enriched post-acute COVID-19 but do not modulate the thrombotic riskClinical Immunology 2023; 257: 109845 doi: 10.1016/j.clim.2023.109845
6
Pradeep Kumar Hanumegowda, Sakthivel Gnanasekaran. Prediction of Work-Related Risk Factors among Bus Drivers Using Machine LearningInternational Journal of Environmental Research and Public Health 2022; 19(22): 15179 doi: 10.3390/ijerph192215179
7
Pierluigi Castelli, Andrea De Ruvo, Andrea Bucciacchio, Nicola D’Alterio, Cesare Cammà, Adriano Di Pasquale, Nicolas Radomski. Harmonization of supervised machine learning practices for efficient source attribution of Listeria monocytogenes based on genomic dataBMC Genomics 2023; 24(1) doi: 10.1186/s12864-023-09667-w
8
Xiaodong Zang, Liandong Feng, Wengang Qin, Weilin Wang, Xiaowei Zang. Using machine learning methods to analyze the association between urinary polycyclic aromatic hydrocarbons and chronic bowel disorders in American adultsChemosphere 2024; 346: 140602 doi: 10.1016/j.chemosphere.2023.140602
9
Johannes Haubold, René Hosch, Gregor Jost, Felix Kreis, Michael Forsting, Hubertus Pietsch, Felix Nensa. AI as a New Frontier in Contrast Media ResearchInvestigative Radiology 2024; 59(2): 206 doi: 10.1097/RLI.0000000000001028
10
Anand Kumar Pandey, Shalja Verma. Radiomics and Radiogenomics in Neuro-Oncology2024; : 211 doi: 10.1016/B978-0-443-18508-3.00005-X
11
Chenyi Zhao, Jie Zhao, Wenlei Wang, Changjiang Yuan, Jie Tang. A novel hybrid ensemble model for mineral prospectivity prediction: A case study in the Malipo W-Sn mineral district, Yunnan Province, ChinaOre Geology Reviews 2024; 168: 106001 doi: 10.1016/j.oregeorev.2024.106001
12
Abdelhady Omar, Atefeh Delnaz, Mazdak Nik-Bakht. Comparative analysis of machine learning techniques for predicting water main failures in the City of KitchenerJournal of Infrastructure Intelligence and Resilience 2023; 2(3): 100044 doi: 10.1016/j.iintel.2023.100044
13
Eric McMullen, Yousif Al-Naser, Jonathan Chung, Jensen Yeung. Machine Learning Applications in Psoriasis Treatment: A Systematic ReviewJournal of Cutaneous Medicine and Surgery 2024;  doi: 10.1177/12034754241238482
14
Emilio Vello, Megan Letourneau, John Aguirre, Thomas E. Bureau. Integrated web portal for non-destructive salt sensitivity detection of Camelina sativa seeds using fluorescent and visible light images coupled with machine learning algorithmsFrontiers in Plant Science 2024; 14 doi: 10.3389/fpls.2023.1303429
15
Michal Pruski. What does it mean for a clinical AI to be just: conflicts between local fairness and being fit-for-purpose?Journal of Medical Ethics 2024; : jme-2023-109675 doi: 10.1136/jme-2023-109675
16
Chaitanya Baliram Pande, Johnbosco C. Egbueri, Romulus Costache, Lariyah Mohd Sidek, Qingzheng Wang, Fahad Alshehri, Norashidah Md Din, Vinay Kumar Gautam, Subodh Chandra Pal. Predictive modeling of land surface temperature (LST) based on Landsat-8 satellite data and machine learning models for sustainable developmentJournal of Cleaner Production 2024; 444: 141035 doi: 10.1016/j.jclepro.2024.141035
17
Miroslav Stojadinovic, Bogdan Milicevic, Slobodan Jankovic. Enhanced PSA Density Prediction Accuracy When Based on Machine LearningJournal of Medical and Biological Engineering 2023; 43(3): 249 doi: 10.1007/s40846-023-00793-0
18
Ju Zhou, Feiyi Li, Xinwu Wang, Heng Yin, Wenjing Zhang, Jiaoyang Du, Haibo Pu. Hyperspectral and Fluorescence Imaging Approaches for Nondestructive Detection of Rice ChlorophyllPlants 2024; 13(9): 1270 doi: 10.3390/plants13091270
19
Taira Batista Luna, Jose Luis García Bello, Agustín Garzón Carbonell, Ana de la Caridad Román Montoya, Alcibíades Lara Lafargue, Héctor Manuel Camué Ciria, Yohandys A. Zulueta. The role of various physiological and bioelectrical parameters for estimating the weight status in infants and juveniles cohort from the Southern Cuba region: a machine learning studyBMC Pediatrics 2024; 24(1) doi: 10.1186/s12887-024-04789-w
20
Yingwen Wu, Yangjian Ji. Identifying firm-specific technology opportunities from the perspective of competitors by using association rule miningJournal of Informetrics 2023; 17(2): 101398 doi: 10.1016/j.joi.2023.101398
21
Miguel Ángel Jiménez García, Richard de Jesús Gil Herrera. Good Practices and New Perspectives in Information Systems and TechnologiesLecture Notes in Networks and Systems 2024; 987: 389 doi: 10.1007/978-3-031-60221-4_37
22
Jan-Mou Lee, Yi-Ping Hung, Kai-Yuan Chou, Cheng-Yun Lee, Shian-Ren Lin, Ya-Han Tsai, Wan-Yu Lai, Yu-Yun Shao, Chiun Hsu, Chih-Hung Hsu, Yee Chao. Artificial intelligence-based immunoprofiling serves as a potentially predictive biomarker of nivolumab treatment for advanced hepatocellular carcinomaFrontiers in Medicine 2022; 9 doi: 10.3389/fmed.2022.1008855
23
Yiheng Shi, Haohan Fan, Li Li, Yaqi Hou, Feifei Qian, Mengting Zhuang, Bei Miao, Sujuan Fei. The value of machine learning approaches in the diagnosis of early gastric cancer: a systematic review and meta-analysisWorld Journal of Surgical Oncology 2024; 22(1) doi: 10.1186/s12957-024-03321-9
24
Cyrel Ontimare Manlises, Jeng-Wen Chen, Chih-Chung Huang. A gated recurrent unit model based on ultrasound images of dynamic tongue movement for determining the severity of obstructive sleep apneaUltrasonics 2024; 141: 107320 doi: 10.1016/j.ultras.2024.107320
25
Wentao Zhang, Wenguang Huang, Jie Tan, Dawei Huang, Jun Ma, Bingdang Wu. Modeling, optimization and understanding of adsorption process for pollutant removal via machine learning: Recent progress and future perspectivesChemosphere 2023; 311: 137044 doi: 10.1016/j.chemosphere.2022.137044
26
Jovitha Wilson, Seyed Ebrahim Hosseini, Shahbaz Pervez. Identification of Fake News in Social Media Using Sentimental Analysis2023 IEEE Industrial Electronics and Applications Conference (IEACon) 2023; : 220 doi: 10.1109/IEACon57683.2023.10370300
27
Shaina Smith, Sabine McConnell. The use of artificial neural networks and decision trees: Implications for health-care researchOpen Computer Science 2024; 14(1) doi: 10.1515/comp-2022-0279
28
Nipun Verma, Arka De, Ajay Duseja. Editorial: Using machine learning to predict significant fibrosis in metabolic dysfunction‐associated steatotic liver disease—authors' replyAlimentary Pharmacology & Therapeutics 2024; 59(7): 896 doi: 10.1111/apt.17913
29
Shaodong Zheng, Lin Jing, Kai Liu, Zhenhao Yu, Zhao Tang, Kaiyun Wang. Crash energy management optimization of high-speed trains by machine learning methodsInternational Journal of Mechanical Sciences 2024; 270: 109108 doi: 10.1016/j.ijmecsci.2024.109108
30
Alvaro Ras-Carmona, Alexander A. Lehmann, Paul V. Lehmann, Pedro A. Reche. Prediction of B cell epitopes in proteins using a novel sequence similarity-based methodScientific Reports 2022; 12(1) doi: 10.1038/s41598-022-18021-1
31
Rui Huang, Shuangcheng Ma, Shengyun Dai, Jian Zheng. Application of Data Fusion in Traditional Chinese Medicine: A ReviewSensors 2023; 24(1): 106 doi: 10.3390/s24010106
32
Arihant Singh, Vivek R Velagala, Tanishq Kumar, Rajoshee R Dutta, Tushar Sontakke. The Application of Deep Learning to Electroencephalograms, Magnetic Resonance Imaging, and Implants for the Detection of Epileptic Seizures: A Narrative ReviewCureus 2023;  doi: 10.7759/cureus.42460
33
Ben Li, Badr Aljabri, Raj Verma, Derek Beaton, Naomi Eisenberg, Douglas S. Lee, Duminda N. Wijeysundera, Thomas L. Forbes, Ori D. Rotstein, Charles de Mestral, Muhammad Mamdani, Graham Roche-Nagle, Mohammed Al-Omran. Using machine learning to predict outcomes following open abdominal aortic aneurysm repairJournal of Vascular Surgery 2023; 78(6): 1426 doi: 10.1016/j.jvs.2023.08.121
34
Matthew I. Miller, Ludy C. Shih, Vijaya B. Kolachalama. Machine Learning in Clinical Trials: A Primer with Applications to NeurologyNeurotherapeutics 2023; 20(4): 1066 doi: 10.1007/s13311-023-01384-2
35
Zaid Alhulaybi, Muhammad Martuza, Sayeed Rushd. Modeling the Mechanical Properties of a Polymer-Based Mixed-Matrix Membrane Using Deep Learning Neural NetworksChemEngineering 2023; 7(5): 80 doi: 10.3390/chemengineering7050080
36
Ibrahem Albalkhi, Aashim Bhatia, Nico Lösch, Robert Goetti, Kshitij Mankad. Current state of radiomics in pediatric neuro-oncology practice: a systematic reviewPediatric Radiology 2023; 53(10): 2079 doi: 10.1007/s00247-023-05679-6
37
Hang Thi Thuy Tran, Quang Hao Nguyen, Ty Huu Pham, Giang Thi Huong Ngo, Nho Tran Dinh Pham, Tung Gia Pham, Chau Thi Minh Tran, Thang Nam Ha. Novel Learning of Bathymetry from Landsat 9 Imagery Using Machine Learning, Feature Extraction and Meta-Heuristic Optimization in a Shallow Turbid LagoonGeosciences 2024; 14(5): 130 doi: 10.3390/geosciences14050130
38
Rushad Patell, Jeffrey I. Zwicker, Rohan Singh, Simon Mantha. Machine learning in cancer-associated thrombosis: hype or hope in untangling the clotBleeding, Thrombosis and Vascular Biology 2024; 3(s1) doi: 10.4081/btvb.2024.123
39
Abdul Majed Sajib, Mir Talas Mahammad Diganta, Md. Moniruzzaman, Azizur Rahman, Tomasz Dabrowski, Md Galal Uddin, Agnieszka I. Olbert. Assessing water quality of an ecologically critical urban canal incorporating machine learning approachesEcological Informatics 2024; 80: 102514 doi: 10.1016/j.ecoinf.2024.102514
40
Laily Azyan Ramlan, Wan Mimi Diyana Wan Zaki, Haliza Abdul Mutalib, Aini Hussain, Aouache Mustapha. Cataract Detection using Pupil Patch Classification and Ruled-based System in Anterior Segment Photographed Images2023 IEEE 13th Symposium on Computer Applications & Industrial Electronics (ISCAIE) 2023; : 124 doi: 10.1109/ISCAIE57739.2023.10165004
41
Lhoussaine El Mezouary, Abdessamad Hadri, Mohamed Hakim Kharrou, Younes Fakır, Abderrahman Elfarchouni, Lhoussaine Bouchaou, Abdelghani Chehbouni. Contribution to advancing aquifer geometric mapping using machine learning and deep learning techniques: a case study of the AL Haouz-Mejjate aquifer, Marrakech, MoroccoApplied Water Science 2024; 14(5) doi: 10.1007/s13201-024-02162-x
42
Yao Yao, Chuanliang Jia, Haicheng Zhang, Yakui Mou, Cai Wang, Xiao Han, Pengyi Yu, Ning Mao, Xicheng Song. Applying a nomogram based on preoperative CT to predict early recurrence of laryngeal squamous cell carcinoma after surgeryJournal of X-Ray Science and Technology 2023; 31(3): 435 doi: 10.3233/XST-221320