Published on in Vol 27 (2025)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/78306, first published
.
Diagnostic Performance of Computed Tomography–Based Artificial Intelligence for Early Recurrence of Cholangiocarcinoma: Systematic Review and Meta-Analysis
Diagnostic Performance of Computed Tomography–Based Artificial Intelligence for Early Recurrence of Cholangiocarcinoma: Systematic Review and Meta-Analysis
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- Cong F, Tian K, Gao Q, Wang F, Sun P, Xu N. CT Radiomics–Based Machine Learning Model for Predicting Capsular and Neural Invasion in Thyroid Carcinoma: Diagnostic Accuracy Study. JMIR Medical Informatics 2026;14:e77349 View
- Mo C, Hu X, Yuan Z, Liu T. Advances in In Vitro Diagnostics for Cholangiocarcinoma: From Biomarker Discovery to Artificial Intelligence. International Journal of Molecular Sciences 2026;27(9):3779 View
- Matuschewski N, Baker W, Chapiro J, Calderaro J. Artificial intelligence and personalised medicine in liver cancer. Journal of Hepatology 2026 View
- Manganaro L, De Sario G, Carpino G, Frey L, Gaudio E, Syn W, Alvaro D, Cardinale V. Digital and Biological Twins in Cholangiocarcinoma: From Translational Research to Precision Medicine—A Narrative Review. Livers 2026;6(4):80 View