Health Technology/clinical-trials

Completed Oculomics Study Demonstrates AI Detection of Hepatobiliary Disease Through Retinal Imaging — Implications for Early Screening

247 Health News Editorial

·

18 May 2026

·

3 min read

·clinical-trials

Completed Chinese study demonstrates AI analysis of retinal images can detect hepatobiliary diseases with high accuracy. Research validates oculomics approach for non-invasive systemic disease screening through routine eye examinations.

Originally reported by ClinicalTrials.gov

References

  1. 1.Zhongshan Ophthalmic Center. (2024). Detection of Systemic Diseases Such as Hepatobiliary Diseases From Ocular Images Via Deep Learning. ClinicalTrials.gov. NCT07581925. https://clinicaltrials.gov/study/NCT07581925
  2. 2.Wagner, S. K., Fu, D. J., Faes, L., Liu, X., Huemer, J., Khalid, H., ... & Keane, P. A. (2021). Insights into systemic disease through retinal imaging-based oculomics. Translational Vision Science & Technology, 10(6), 6. https://doi.org/10.1167/tvst.10.6.6
  3. 3.Rim, T. H., Lee, G., Kim, Y., Tham, Y. C., Lee, C. J., Baik, S. J., ... & Cheung, C. Y. (2020). Deep learning in ophthalmology: The technical and clinical considerations. Progress in Retinal and Eye Research, 72, 100759. https://doi.org/10.1016/j.preteyeres.2020.100759
  4. 4.Hajian-Tilaki, K. (2013). Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian Journal of Internal Medicine, 4(2), 627-635. PMC3755824
  5. 5.Asrani, S. K., Devarbhavi, H., Eaton, J., & Kamath, P. S. (2019). Burden of liver diseases in the world. Journal of Hepatology, 70(1), 151-171. https://doi.org/10.1016/j.jhep.2019.01.020
  6. 6.European Association for the Study of the Liver. (2021). EASL Clinical Practice Guidelines on non-invasive tests for evaluation of liver disease severity and prognosis—2021 update. Journal of Hepatology, 75(3), 659-689. https://doi.org/10.1016/j.jhep.2021.05.025
  7. 7.Cheung, C. Y., Xu, D., Cheng, C. Y., Sabanayagam, C., Tham, Y. C., Yu, M., ... & Wong, T. Y. (2021). A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre. Nature Biomedical Engineering, 5(6), 498-508. https://doi.org/10.1038/s41551-020-00626-4
Share:XLinkedIn
2

247 Health News Editorial

247 Health News is a medical intelligence platform delivering evidence-based research appraisals, clinical trial monitoring, and health technology news for healthcare professionals.

This content is for educational purposes for healthcare professionals only and does not constitute clinical advice. Clinical decisions should be based on individual patient assessment, current guidelines, and appropriate specialist consultation. Editorial Standards · Privacy Policy · Terms of Service