Using Machine Learning to Improve the Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System Diagnosis of Hepatocellular Carcinoma in Indeterminate Liver Nodules.
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| Title: | Using Machine Learning to Improve the Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System Diagnosis of Hepatocellular Carcinoma in Indeterminate Liver Nodules. |
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| Authors: | Hoopes JR; Department of Pharmacology, Physiology, and Cancer Biology, Division of Biostatistics and Bioinformatics, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA., Lyshchik A; Department of Radiology, Thomas Jefferson University, Philadelphia PA, USA., Xiao TS; Department of Radiology, Thomas Jefferson University, Philadelphia PA, USA., Berzigotti A; Department of Visceral Surgery and Medicine, Bern University Hospital, University of Bern, Bern, Switzerland., Fetzer DT; UT Southwestern Medical Center, Dallas, TX, USA., Forsberg F; Department of Radiology, Thomas Jefferson University, Philadelphia PA, USA., Sidhu PS; Department of Imaging Sciences, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK; Department of Radiology, King's College Hospital, London, UK., Wessner CE; Department of Radiology, Thomas Jefferson University, Philadelphia PA, USA., Wilson SR; Department of Radiology, University of Calgary, Calgary, Canada., Keith SW; Department of Pharmacology, Physiology, and Cancer Biology, Division of Biostatistics and Bioinformatics, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA; Sidney Kimmel Comprehensive Cancer Center at Thomas Jefferson University, Philadelphia, PA, USA. Electronic address: scott.keith@jefferson.edu. |
| Source: | Ultrasound in medicine & biology [Ultrasound Med Biol] 2025 Nov; Vol. 51 (11), pp. 1953-1960. Date of Electronic Publication: 2025 Aug 11. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Pergamon Press Country of Publication: England NLM ID: 0410553 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-291X (Electronic) Linking ISSN: 03015629 NLM ISO Abbreviation: Ultrasound Med Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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