Clinical application of artificial intelligence in corneal transplantation
Medical hypothesis, discovery & innovation in optometry,
Vol. 7 No. 2 (2026),
24 July 2026
,
Page 80-93
https://doi.org/10.51329/mehdioptometry249
Abstract
Background: Artificial intelligence (AI) is increasingly being incorporated into ophthalmic practice and shows promise in improving diagnostic accuracy, patient selection, surgical planning, and postoperative care. In corneal transplantation, AI-based tools may help clinicians make more informed decisions throughout the patient journey. This review examines the current evidence on the use of AI in corneal transplantation, with a focus on its clinical applications, existing challenges, and future potential for routine practice.Methods: A literature review was conducted to identify studies evaluating the use of AI in corneal transplantation. Searches were conducted in PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases for articles published up to 20 August 2025. The search strategy combined terms related to “artificial intelligence”, “machine learning”, and “deep learning” with “corneal transplantation” and “keratoplasty”.
Results: Twenty studies met the inclusion criteria. Most studies used imaging modalities such as anterior segment optical coherence tomography (AS-OCT), specular microscopy, or surgical videos, while others incorporated structured clinical information or multimodal datasets. Descemet membrane endothelial keratoplasty (DMEK) was the most commonly investigated procedure. AI approaches predominantly utilized supervised methodologies, spanning deep learning networks and traditional machine learning algorithms alongside a limited application of unsupervised and survival-based models. Common objectives included predicting graft outcomes, detecting and quantifying graft detachment, identifying factors associated with graft failure, and assisting surgical decision-making. Classification and image segmentation were the predominant analytical tasks. AI models evidenced favorable predictive and analytical performance across a broad range of clinical applications, highlighting their potential to support preoperative risk stratification, intraoperative decision-making, postoperative monitoring, and long-term graft outcome prediction.
Conclusions: The current literature suggests that AI has the potential to become an important clinical support tool in corneal transplantation. By integrating imaging, biometric, and clinical data, AI models may help predict graft survival, identify patients at higher risk of complications, and facilitate more personalized management strategies. Although the reported results are encouraging, several barriers remain, including limited external validation, lack of standardized datasets, and concerns about model interpretability. Future work should focus on developing robust, explainable, and generalizable AI systems through multicenter collaboration and multimodal data integration to support their safe and effective adoption in clinical practice.
Keywords:
- machine learning
- AI (artificial intelligence)
- deep learning
- machine
- Corneas
- corneal transplantations
- penetrating keratoplasty
- lamellar keratoplasty
- descemet stripping endothelial keratoplasty
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3. Maghsoudlou P, Sood G, Gurnani B, Akhondi H. Cornea Transplantation. 2024 Feb 24. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2026 Jan–. PMID: 30969512.
4. Mishra SK, Joshi A, Ginu PM, Sati A, Kumar SV. Corneal transplantation: A walk to vision. Med J Armed Forces India. 2023 Nov-Dec;79(6):645-650. doi: 10.1016/j.mjafi.2023.08.010. Epub 2023 Sep 13. PMID: 37981925; PMCID: PMC10654358.
5. Reeves SW, Ellwein LB, Kim T, Constantine R, Lee PP. Keratoconus in the Medicare population. Cornea. 2009 Jan;28(1):40-2. doi: 10.1097/ICO.0b013e3181839b06. PMID: 19092403; PMCID: PMC2723840.
6. Dorado-Cortez O, Poinard S, Epinat M, Collange F, Ninotta S, Goin P, Perrot JL, Gain P, Pollock G, Thuret G. The burden of medical contraindications to corneal donation: Time for review. PLOS Glob Public Health. 2024 Dec 31;4(12):e0003537. doi: 10.1371/journal.pgph.0003537. PMID: 39739771; PMCID: PMC11687701.
7. Liu S, Wong YL, Walkden A. Current Perspectives on Corneal Transplantation. Clin Ophthalmol. 2022 Mar 4;16:631-646. doi: 10.2147/OPTH.S289359. PMID: 35282172; PMCID: PMC8904759.
8. Szkodny D, Wróblewska-Czajka E, Wyl?ga?a A, Nandzik M, Wyl?ga?a E. Incidence of Complications Related to Corneal Graft in a Group of 758 Patients. J Clin Med. 2022 Dec 28;12(1):220. doi: 10.3390/jcm12010220. PMID: 36615021; PMCID: PMC9821265.
9. Zhang LJ, Dana R, Lorch AC, Elze T, Miller JW, Dohlman TH, Oke I; IRIS Registry Analytic Center Consortium. Complications After Pediatric Penetrating Keratoplasty: An IRIS Registry Study. Cornea. 2024 Dec 1;43(12):1555-1559. doi: 10.1097/ICO.0000000000003656. Epub 2024 Aug 13. PMID: 39137435; PMCID: PMC11537838.
10. Minasian M, Ayliffe W. Fixed dilated pupil following deep lamellar keratoplasty (Urrets-Zavalia syndrome). Br J Ophthalmol. 2002 Jan;86(1):115-6. doi: 10.1136/bjo.86.1.115. PMID: 11801517; PMCID: PMC1770988.
11. Zemba M, Stamate AC. Glaucoma after penetrating keratoplasty. Rom J Ophthalmol. 2017 Jul-Sep;61(3):159-165. doi: 10.22336/rjo.2017.30. PMID: 29450392; PMCID: PMC5710032.
12. Price MO, Price DA, Fairchild KM, Price FW Jr. Rate and risk factors for cataract formation and extraction after Descemet stripping endothelial keratoplasty. Br J Ophthalmol. 2010 Nov;94(11):1468-71. doi: 10.1136/bjo.2009.175174. Epub 2010 May 27. PMID: 20508038; PMCID: PMC2976606.
13. Dirisamer M, van Dijk K, Dapena I, Ham L, Oganes O, Frank LE, Melles GR. Prevention and management of graft detachment in descemet membrane endothelial keratoplasty. Arch Ophthalmol. 2012 Mar;130(3):280-91. doi: 10.1001/archophthalmol.2011.343. Epub 2011 Nov 14. PMID: 22084160.
14. Ghafarian S, Koo EH. Long-Term Graft Survival and Visual Outcomes in Deep Anterior Lamellar Keratoplasty (DALK): A Narrative Review. J Ophthalmol. 2026 Feb 23;2026:8120487. doi: 10.1155/joph/8120487. PMID: 41737287; PMCID: PMC12927906.
15. Azevedo Magalhaes O, Shalaby Bardan A, Zarei-Ghanavati M, Liu C. Literature review and suggested protocol for prevention and treatment of corneal graft rejection. Eye (Lond). 2020 Mar;34(3):442-450. doi: 10.1038/s41433-019-0517-9. Epub 2019 Jul 22. PMID: 31332293; PMCID: PMC7042259.
16. Espandar L, Carlson AN. Lamellar keratoplasty: a literature review. J Ophthalmol. 2013;2013:894319. doi: 10.1155/2013/894319. Epub 2013 Oct 7. PMID: 24223301; PMCID: PMC3816057.
17. Malta JB, Soong HK, Shtein R, Banitt M, Musch DC, Sugar A, Mian SI. Femtosecond laser-assisted keratoplasty: laboratory studies in eye bank eyes. Curr Eye Res. 2009 Jan;34(1):18-25. doi: 10.1080/02713680802535255. PMID: 19172466.
18. Aggarwal S, Kumari M, Bhatnagar N. Advancements in keratoplasty: Exploring newer techniques and imaging modalities for enhanced surgical outcomes. Saudi J Ophthalmol. 2024 Mar 1;39(4):337-348. doi: 10.4103/sjopt.sjopt_234_23. PMID: 41367843; PMCID: PMC12685274.
19. Al-Shami K, Almurabi S, Pop A, Vincent C, Popescu A, Pop IC, Bader NS, Faour H, Barhoush R, Karaja S. Emerging technologies in corneal transplantation: Innovations, challenges, and global implications. Transplantation Reports. 2025 Sep 1;10(3):100180. doi: 10.1016/j.tpr.2025.100180.
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