ReviewZhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology2026
[Application and prospects of artificial intelligence from tool empowerment to paradigm reconstruction for whole-course diagnosis and treatment of liver diseases by ultrasound].
Review in Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors.
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Abstract
The research system and clinical decision-making pathways have been systematically reshaped as the application of artificial intelligence (AI) in the field of ultrasonically has become increasingly mature recently for liver disease imaging. Research focus has shifted at the clinical level from low-dimensional classification and diagnostic tasks to high-dimensional, task-driven intelligent diagnosis and treatment. The underlying algorithms are undergoing a profound transition at the technological level from single-modality to multi-modal collaboration and from isolated feature extraction to spatiotemporal sequential reasoning. Therefore, to provide a forward-looking analysis and reflection on future development trends and existing challenges, this article systematically reviews the latest research progress of AI in the field of liver disease in terms of four aspects of ultrasonography: early-stage screening, precise diagnosis, personalized treatment, and prognostic monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.