LI-RADS-aligned artificial intelligence for liver cancer diagnosis: methods, evidence, and clinical readiness.
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| Title: | LI-RADS-aligned artificial intelligence for liver cancer diagnosis: methods, evidence, and clinical readiness. |
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| Authors: | Abuhassan Q; Department of Pharmaceutics and Pharmaceutical Technology, School of Pharmacy, University of Jordan, Amman, 11942, Jordan., Oriquat G; Faculty of Allied Medical Sciences, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan. goreqat@ammanu.edu.jo., Ganesan S; Department of Chemistry and Biochemistry, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India., Kanwar JB; Department of Endocrinology, IMS and SUM Hospital, Siksha 'O' Anusandhan, Bhubaneswar, Odisha, 751003, India., Kumar VR; Department of Biotechnology, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India., Sharma V; Department of Biotechnology, University Institute of Biotechnology, Chandigarh University, Mohali,, Punjab,, India., Chauhan AS; Uttaranchal Institute of Pharmaceutical Sciences, Division of Research and Innovation, Uttaranchal University, Dehradun, Uttarakhand, India., Abdullaev T; Department of Oral Surgery and Dental Implantology, Samarkand State Medical University, Samarkand, Uzbekistan. |
| Source: | Abdominal radiology (New York) [Abdom Radiol (NY)] 2026 Jul; Vol. 51 (7), pp. 3446-3460. Date of Electronic Publication: 2025 Dec 19. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Springer Country of Publication: United States NLM ID: 101674571 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2366-0058 (Electronic) NLM ISO Abbreviation: Abdom Radiol (NY) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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