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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
Number Citing Articles
1
Pablo Guillermo Hernández-Almonacid, Ximena Marín-Quintero. Artificial intelligence in metabolic dysfunction-associated steatotic liver disease: Transforming diagnosis and therapeutic approachesWorld Journal of Gastroenterology 2026; 32(2): 111737 doi: 10.3748/wjg.v32.i2.111737
2
Nicholas Viceconti, Silvia Andaloro, Mattia Paratore, Sara Miliani, Giulia D’Acunzo, Giuseppe Cerniglia, Fabrizio Mancuso, Elena Melita, Antonio Gasbarrini, Laura Riccardi, Matteo Garcovich. Harnessing artificial intelligence for the assessment of liver fibrosis and steatosis <i>via</i> multiparametric ultrasoundWorld Journal of Gastroenterology 2026; 32(2): 113059 doi: 10.3748/wjg.v32.i2.113059
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 residentsPLOS One 2025; 20(7): e0327739 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 SampleJGH 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 comingInternational Journal of Computer Assisted Radiology and Surgery 2025;  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 cholangiocarcinomaScientific 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 UltrasoundUltrasound in Medicine & Biology 2025; 51(11): 1865 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 hospitalsChinese Medical Journal 2024; 137(24): 3083 doi: 10.1097/CM9.0000000000003436
9
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 Carcinoma2025 19th International Conference on Complex Medical Engineering (CME) 2025; : 171 doi: 10.1109/CME67420.2025.11239404
10
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 DiseaseRadiology 2023; 309(2) doi: 10.1148/radiol.223146
11
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 reviewPLOS Neglected Tropical Diseases 2024; 18(3): e0012033 doi: 10.1371/journal.pntd.0012033
12
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 microvascularizationClinical Hemorheology and Microcirculation 2025;  doi: 10.1177/13860291251375539
13
Stacey May, Christina Hendricks, Diana Mishler, Matthew Schwartz, Nancy Barge, Kristin Pahl Kenozy, Anne-Marie Lugossy. Radiology in Global Health2025; : 117 doi: 10.1007/978-3-031-86485-8_11
14
Binbin Wu. Diagnostic superiority of contrast-enhanced ultrasound combined with elastography for early hepatocellular carcinoma in cirrhotic patientsAmerican Journal of Translational Research 2025; 17(10): 7957 doi: 10.62347/EVRW8961
15
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 ImagingUltrasound in Medicine & Biology 2025; 51(3): 428 doi: 10.1016/j.ultrasmedbio.2024.10.016
16
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 learningBMC Cancer 2024; 24(1) doi: 10.1186/s12885-024-12546-6
17
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-MakingLife 2024; 14(9): 1199 doi: 10.3390/life14091199
18
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 nodulesFrontiers in Endocrinology 2025; 16 doi: 10.3389/fendo.2025.1639017
19
Laxmi Rani, Garima Jain, Pooja Mathur, Shaveta Ahalwat, Shailendra Bhatt. Advances in Disaster Management, Volume 2Springer Transactions in Civil and Environmental Engineering 2025; : 185 doi: 10.1007/978-981-96-4047-8_18
20
Fei Xia, Wei Wei, Junli Wang, Yayang Duan, Kun Wang, Chaoxue Zhang. Machine learning model for non-alcoholic steatohepatitis diagnosis based on ultrasound radiomicsBMC Medical Imaging 2024; 24(1) doi: 10.1186/s12880-024-01398-y
21
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 2024Frontiers in Medicine 2025; 12 doi: 10.3389/fmed.2025.1698366
22
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 literatureJournal of Gastroenterology and Hepatology 2024; 39(10): 1994 doi: 10.1111/jgh.16663
23
C Uma, K Gobikanila, P R Jeyaramraja, Syraji Yonas. Metal nanoparticles in liver cancer therapy: Advances, challenges, and future directionsNext Research 2025; 2(3): 100421 doi: 10.1016/j.nexres.2025.100421
24
Zhao-Chun Chi. Application and prospect of artificial intelligence in diagnosis, treatment, and prognosis of liver cancerWorld Chinese Journal of Digestology 2025; 33(6): 429 doi: 10.11569/wcjd.v33.i6.429
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25
Wenpeng Huang, Yushuo Peng, Lei Kang. Advancements of non‐invasive imaging technologies for the diagnosis and staging of liver fibrosis: Present and futureVIEW 2024; 5(4) doi: 10.1002/VIW.20240010
26
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 OutcomesBrain Sciences 2025; 15(5): 494 doi: 10.3390/brainsci15050494
27
Jingpu Zhao, Yongfeng Xu. PITX1 plays essential functions in cancerFrontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1253238
28
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 metadataThe Visual Computer 2025; 41(13): 11445 doi: 10.1007/s00371-025-04100-7
29
Fei Xia, Kun Wang, Yuhe Wang, Chaoxue Zhang, Junli Wang. Ultrasound and SWE-based transfer learning for predicting fibrotic NASHScientific Reports 2025; 15(1) doi: 10.1038/s41598-025-28753-5
30
Jian-Jun Lou, Jing Zeng. Artificial intelligence applications for managing metabolic dysfunction-associated steatotic liver disease: Current status and future prospectsWorld Journal of Gastroenterology 2025; 31(47): 111900 doi: 10.3748/wjg.v31.i47.111900
31
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 RadiologistsIEEE Access 2025; 13: 178725 doi: 10.1109/ACCESS.2025.3617778