Article Sidebar

PDF
Date Published: 22/07/2024
Abstract Views: 0
Views PDF: 0
DOI: https://doi.org/10.51298/vmj.v540i3.10511
Issue
Vol. 540 No. 3 (2024)
Section
Các bài báo
How to Cite
Lương, T. H. H., Pham, T. V., Đặng , Đức M., Ninh , S. Q., & Pham, G. K. (2024). DIAGNOSTIC RESULTS OF DIABETIC RETINOPATHY BY USING ARTIFICIAL INTELLIGENCE AT THAI NGUYEN NATIONAL HOSPITAL. Vietnam Medical Journal, 540(3). https://doi.org/10.51298/vmj.v540i3.10511

DIAGNOSTIC RESULTS OF DIABETIC RETINOPATHY BY USING ARTIFICIAL INTELLIGENCE AT THAI NGUYEN NATIONAL HOSPITAL

Thị Hải Hà Lương, Trọng Văn Pham, Đức Minh Đặng , Sỹ Quỳnh Ninh , Giáng Kiều Pham

Main Article Content

Abstract

Objective: Evaluating the results of Diabetic Retinopathy diagnosis using Artificial intelligence at Thai Nguyen National Hospital. Patients and methods: 1012 patients with diabetes type 2 (1943 eye) at Thai Nguyen National Hospital. A cross-sectional study. Results: - There are 13.8% of eyes with diabetic retinopathy, of which the most common damage are microaneurysms, retinal exudates and retinal hemorrhages. - There are 10,6% eye of  proliferative DR and 89,4% eye of  non-proliferative DR with different levels, in there Mild non-proliferative DR are highest rate with 40,9%. Conclusion: Artificial intelligence can be used to diagnose DR for patients with diabetes type 2 are monitored and treated as outpatients at provincial hospitals.

Article Details

Keywords

Diabetes type 2, Artificial intelligence (AI), Diabetic retinopathy (DR)

References

1. World, Health, Organization. Diabetes, accessed 21/09/2017 from http://www.who.int/ diabetes/en/. 2017.
2. World, Health, Organization. Blindness and vision impairment. Report on IAPB conference, . 2019;2019.
3. Hoàng Thị Phúc, Phạm Trọng Văn, Nguyễn Hữu Quốc Nguyên. Nghiên cứu tình hình bệnh võng mạc đái tháo đường tại Việt Nam. Kỷ yếu hội nghị Nhãn khoa. 2010;170.
4. Holijah Uy CF, Ameer Hohlfeld, et al. Diagnostic test accuracy of artificial intelligence in screening for referable diabetic retinopathy in real-world settings: A systematic review and meta-analysis. PLOS Global Public Health. 2023;3(9): e0002160:1-23.
5. Chufeng Gu YW, Yan Jiang, et al. Application of artificial intelligence system for screening multiple fundus diseases in Chinese primary healthcare settings: a real-world, multicentre and cross-sectional study of 4795 cases. Br J Ophthalmol 2023;2023; 0:1–8.
6. Marco Lupidi LD, Daniela Fruttini, et al. Artifcial intelligence in diabetic retinopathy screening: clinical assessment using handheld fundus camera in a real‑life setting. Acta Diabetologica 2023;(2023) 60:1083–1088
7. Wong TY, Sun J, Kawasaki R. Guideline on Diabetic Eye Care. American Academy of Ophthalmology. 2018;125(10):1608-1622.
8. K Viswanath MS MMG. Diabetes retinopathy: Clinical findings and management. Community Eye Health. 2013;Vol 16 No.46:pp.21-24.
9. Hiền LT. Mô tả đặc điểm lâm sàng, cận lâm sàng bệnh võng mạc đái tháo đường tại bệnh viện đa khoa tỉnh Hòa Bình năm 2020 và một số yếu tố liên quan. Luận văn Chuyên khoa cấp 2, Trường Đại học Y Hà Nội. 2020.