World Journal of Gastroenterology - Baishideng Publishing Group

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For:	Cao LL, Peng M, Xie X, Chen GQ, Huang SY, Wang JY, Jiang F, Cui XW, Dietrich CF. Artificial intelligence in liver ultrasound. World J Gastroenterol 2022; 28(27): 3398-3409 [PMID: 36158262 DOI: 10.3748/wjg.v28.i27.3398]
URL:	https://www.wjgnet.com/1007-9327/full/v28/i27/3398.htm

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Number	Citing Articles
1	Ximena Marín-Quintero, Pablo Guillermo Hernández-Almonacid. Artificial intelligence in metabolic dysfunction-associated steatotic liver disease: Transforming diagnosis and therapeutic approaches. World Journal of Gastroenterology 2026; 32(2): 111737 doi: 10.3748/wjg.v32.i2.111737 Abstract(91) \| Core Tip(77) \| Full Article(HTML)(431) \| Full Article (PDF)-1071K(329) \| Full Article with Cover (PDF)-1414K(28) \| Full Article (XML)-236K(34) \| Audio-1587K(5) \| Peer-Review Report-321K(36) \| Answering Reviewers-263K(64) \| Times Cited (3) \| Total Visits (946) \| Open
2	Nicholas Viceconti, Silvia Andaloro, Mattia Paratore, Sara Miliani, Giulia D’Acunzo, Giuseppe Cerniglia, Fabrizio Mancuso, Elena Melita, Matteo Garcovich, Laura Riccardi, Antonio Gasbarrini. Harnessing artificial intelligence for the assessment of liver fibrosis and steatosis <i>via</i> multiparametric ultrasound. World Journal of Gastroenterology 2026; 32(2): 113059 doi: 10.3748/wjg.v32.i2.113059 Abstract(78) \| Core Tip(78) \| Full Article(HTML)(481) \| Full Article (PDF)-1485K(95) \| Full Article with Cover (PDF)-1828K(98) \| Full Article (XML)-290K(38) \| Audio-242K(15) \| Peer-Review Report-196K(32) \| Answering Reviewers-153K(47) \| Times Cited (1) \| Total Visits (901) \| Open
3	Rong Liu, Lei Li, Ying Zhou, Lu Xiong, Aamir Ijaz. The application of CBL and mind mapping combined with Mini-CEX teaching mode in the cultivation of clinical competence of ultrasound residents. PLOS One 2025; 20(7) doi: 10.1371/journal.pone.0327739
4	Alexander A. Huang, Samuel Y. Huang. The Visualization of the Importance of Covariance Importance in a Machine Learning Model for Advanced Liver Fibrosis in a Nationally Representative Sample. JGH Open 2025; 9(7) doi: 10.1002/jgh3.70200
5	Michael Friebe. AI in radiology and interventions: a structured narrative review of workflow automation, accuracy, and efficiency gains of today and what’s coming. International Journal of Computer Assisted Radiology and Surgery 2025; 21(1) doi: 10.1007/s11548-025-03547-2
6	Roongruedee Chaiteerakij, Darlene Ariyaskul, Kittipat Kulkraisri, Terapap Apiparakoon, Sasima Sukcharoen, Oracha Chaichuen, Phaiboon Pensuwan, Thodsawit Tiyarattanachai, Rungsun Rerknimitr, Sanparith Marukatat. Artificial intelligence for ultrasonographic detection and diagnosis of hepatocellular carcinoma and cholangiocarcinoma. Scientific Reports 2024; 14(1) doi: 10.1038/s41598-024-71657-z
7	Ole Graumann, Wu Cui Xin, Adrian Goudie, Michael Blaivas, Barbara Braden, Susan Campbell Westerway, Maria Cristina Chammas, Yi Dong, Odd Helge Gilja, Peter Ching-Chang Hsieh, An Jiang Tian, Ping Liang, Kathleen Möller, Christian Pállson Nolsøe, Adrian Săftoiu, Christoph Frank Dietrich. Artificial Intelligence in Abdominal, Gynecological, Obstetric, Musculoskeletal, Vascular and Interventional Ultrasound. Ultrasound in Medicine & Biology 2025; 51(11) doi: 10.1016/j.ultrasmedbio.2025.07.008
8	Ke Fan, Lei Yang, Fei Ren, Xueyuan Zhang, Bo Liu, Ze Zhao, Jianwen Gu. Intelligent imaging technology applications in multidisciplinary hospitals. Chinese Medical Journal 2024; 137(24) doi: 10.1097/CM9.0000000000003436
9	Xuping Zhang, Qingyuan Zhang, Tao Zhang, Ge Song, Peng Wang. Fractal-guided multi-scale contrastive learning for robust liver tumor classification in ultrasound. Engineering Applications of Artificial Intelligence 2026; 178 doi: 10.1016/j.engappai.2026.115047
10	Yali Liang, Jie Yang, Xian Wang, Jingchuan Du, Sitian Wang, Peirun Wu, Weiwei Zhang. Clinical Applications and Research Advances of AI-Assisted Radiomics-Based Diagnosis for Hepatocellular Carcinoma. 2025 19th International Conference on Complex Medical Engineering (CME) 2025; doi: 10.1109/CME67420.2025.11239404
11	Arinc Ozturk, Viksit Kumar, Theodore T. Pierce, Qian Li, Masoud Baikpour, Ivan Rosado-Mendez, Michael Wang, Peng Guo, Scott Schoen, Yuyang Gu, Sunethra Dayavansha, Joseph R. Grajo, Anthony E. Samir. The Future Is Beyond Bright: The Evolving Role of Quantitative US for Fatty Liver Disease. Radiology 2023; 309(2) doi: 10.1148/radiol.223146
12	Eloise S. Ockenden, Sandrena Ruth Frischer, Huike Cheng, J. Alison Noble, Goylette F. Chami, Elizabeth J. Carlton. The role of point-of-care ultrasound in the assessment of schistosomiasis-induced liver fibrosis: A systematic scoping review. PLOS Neglected Tropical Diseases 2024; 18(3) doi: 10.1371/journal.pntd.0012033
13	Laura S Kupke, Paul Kupke, Nina Käser, Moritz K Brandenstein, Liang Zhang, Christian Stroszczynski, Ernst-Michael Jung. Contrast-enhanced ultrasound perfusion quantification of solid liver lesions: First intraoperative characterization of tumor microvascularization. Clinical Hemorheology and Microcirculation 2025; 91(1) doi: 10.1177/13860291251375539
14	Stacey May, Christina Hendricks, Diana Mishler, Matthew Schwartz, Nancy Barge, Kristin Pahl Kenozy, Anne-Marie Lugossy. Radiology in Global Health. 2025; doi: 10.1007/978-3-031-86485-8_11
15	Binbin Wu. Diagnostic superiority of contrast-enhanced ultrasound combined with elastography for early hepatocellular carcinoma in cirrhotic patients. American Journal of Translational Research 2025; 17(10) doi: 10.62347/EVRW8961
16	Xin Wu Cui, Adrian Goudie, Michael Blaivas, Young Jun Chai, Maria Cristina Chammas, Yi Dong, Jonathon Stewart, Tian-An Jiang, Ping Liang, Chandra M. Sehgal, Xing-Long Wu, Peter Ching-Chang Hsieh, Saftoiu Adrian, Christoph F. Dietrich. WFUMB Commentary Paper on Artificial intelligence in Medical Ultrasound Imaging. Ultrasound in Medicine & Biology 2025; 51(3) doi: 10.1016/j.ultrasmedbio.2024.10.016
17	Binqian Zhou, Jianxin Liu, Yaqin Yang, Xuewei Ye, Yang Liu, Mingfeng Mao, Xiaofeng Sun, Xinwu Cui, Qin Zhou. Ultrasound-based nomogram to predict the recurrence in papillary thyroid carcinoma using machine learning. BMC Cancer 2024; 24(1) doi: 10.1186/s12885-024-12546-6
18	Rute Santos, Raquel Reis. Ultrasound Elastography in Chronic Liver Disease: From Clinical Applications to Quality Assurance and Future Perspectives. Diagnostics 2026; 16(15) doi: 10.3390/diagnostics16152303
19	Laura S. Kupke, Ivor Dropco, Markus Götz, Paul Kupke, Friedrich Jung, Christian Stroszczynski, Ernst-Michael Jung. Contrast-Enhanced Intraoperative Ultrasound Shows Excellent Performance in Improving Intraoperative Decision-Making. Life 2024; 14(9) doi: 10.3390/life14091199
20	Ramu V, Aditya Mandloi, M. Sujatha, E. Sreedevi, R Sujitha, Vivekanandhan V. AI Systems for Non-Invasive Liver Fibrosis Diagnosis using Ultrasound Imaging. 2025 5th International Conference on Evolutionary Computing and Mobile Sustainable Networks (ICECMSN) 2025; doi: 10.1109/ICECMSN68058.2025.11382972
21	Linlin Shao, Lili Zhang, Lifang Liu, Fangfang Sun, Hongyu Li, Tongfeng Liu, Feng Hu, Lirong Zhao. Multimodal radiomics model with triple -timepoint contrast-enhanced ultrasound for precise diagnosis of C-TIRADS 4 thyroid nodules. Frontiers in Endocrinology 2025; 16 doi: 10.3389/fendo.2025.1639017
22	Laxmi Rani, Garima Jain, Pooja Mathur, Shaveta Ahalwat, Shailendra Bhatt. Advances in Disaster Management, Volume 2. Springer Transactions in Civil and Environmental Engineering 2025; doi: 10.1007/978-981-96-4047-8_18
23	Fei Xia, Wei Wei, Junli Wang, Yayang Duan, Kun Wang, Chaoxue Zhang. Machine learning model for non-alcoholic steatohepatitis diagnosis based on ultrasound radiomics. BMC Medical Imaging 2024; 24(1) doi: 10.1186/s12880-024-01398-y
24	Biting Chen, Yinlu Wang, Xuhuan Xie, Boyan Fan, Wen Zhang, Guixiang Sun. Trends in AI-based diagnosis and intervention of metabolic diseases: a bibliometric analysis of the literature from 2000 to 2024. Frontiers in Medicine 2025; 12 doi: 10.3389/fmed.2025.1698366
25	Odysseas P. Chatzipanagiotou, Constantinos Loukas, Michail Vailas, Nikolaos Machairas, Stylianos Kykalos, Georgios Charalampopoulos, Dimitrios Filippiadis, Evangellos Felekouras, Dimitrios Schizas. Artificial intelligence in hepatocellular carcinoma diagnosis: a comprehensive review of current literature. Journal of Gastroenterology and Hepatology 2024; 39(10) doi: 10.1111/jgh.16663
26	C Uma, K Gobikanila, P R Jeyaramraja, Syraji Yonas. Metal nanoparticles in liver cancer therapy: Advances, challenges, and future directions. Next Research 2025; 2(3) doi: 10.1016/j.nexres.2025.100421
27	Zhao-Chun Chi. Application and prospect of artificial intelligence in diagnosis, treatment, and prognosis of liver cancer. World Chinese Journal of Digestology 2025; 33(6) doi: 10.11569/wcjd.v33.i6.429 Abstract(266) \| Core Tip(320) \| Full Article(HTML)(1992) \| Times Cited (0) \| Total Visits (3003) \| Open
28	Wenpeng Huang, Yushuo Peng, Lei Kang. Advancements of non‐invasive imaging technologies for the diagnosis and staging of liver fibrosis: Present and future. VIEW 2024; 5(4) doi: 10.1002/VIW.20240010
29	José E. Valerio, Guillermo de Jesús Aguirre Vera, Maria P. Fernandez Gomez, Jorge Zumaeta, Andrés M. Alvarez-Pinzon. AI-Driven Advances in Parkinson’s Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes. Brain Sciences 2025; 15(5) doi: 10.3390/brainsci15050494
30	Jingpu Zhao, Yongfeng Xu. PITX1 plays essential functions in cancer. Frontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1253238
31	Pinqi Fang, Dong Lang, Di Cheng, Zhouyu Guan, Yiting Wu, Yulian Zhang, Tingting Hu, Yuqian Bao, Huating Li, Chengxing Shen, Jun Pu, Bin Sheng, Jie Shen. Multimodal and multi-time-point fusion approach for automated diagnosis and grading of carotid atherosclerosis using bilateral ultrasound images and metadata. The Visual Computer 2025; 41(13) doi: 10.1007/s00371-025-04100-7
32	Fei Xia, Kun Wang, Yuhe Wang, Chaoxue Zhang, Junli Wang. Ultrasound and SWE-based transfer learning for predicting fibrotic NASH. Scientific Reports 2025; 15(1) doi: 10.1038/s41598-025-28753-5
33	Jing Zeng, Jian-Jun Lou. Artificial intelligence applications for managing metabolic dysfunction-associated steatotic liver disease: Current status and future prospects. World Journal of Gastroenterology 2025; 31(47): 111900 doi: 10.3748/wjg.v31.i47.111900 Abstract(94) \| Core Tip(95) \| Full Article(HTML)(601) \| Full Article (PDF)-1182K(209) \| Full Article with Cover (PDF)-1436K(433) \| Full Article (XML)-180K(43) \| Audio-357K(20) \| Peer-Review Report-245K(40) \| Answering Reviewers-166K(46) \| Times Cited (2) \| Total Visits (1358) \| Open
34	Fahad Muflih Alshagathrh, Haider Dhia Zubaydi, Mahmood Alzubaidi, Abdulaziz Alosaimi, Raneem Mohammed Al Saqer, Abdullah Mutlaq Alzahrani, Mei Khalid Alfaqiri, Mohamed Rajab Elzahrani, Khalid Alswat, Ali Aldhebaib, Bushra Alahmadi, Meteb Alkubeyyer, Amani Alsadoon, Maram Alkhamash, Jawad Ahmad Alraimi, Jens Schneider, Mowafa Househ. AI-Based Multiclass Grading of Hepatic Steatosis From B-Mode Ultrasound: Generalization Across Modalities and Clinical Comparison With Radiologists. IEEE Access 2025; 13 doi: 10.1109/ACCESS.2025.3617778