This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Deloitte Malta [Internet]. [cited 2023 Oct 21]. The Age of Artificial Intelligence: A brief history... | Deloitte Malta | RPA & AI. Available from: https://www2.deloitte.com/mt/en/pages/rpa-and-ai/articles/mt-age-of-ai-1-a-brief-history.htmlDeloitte Malta [Internet][cited 2023 Oct 21].The Age of Artificial Intelligence: A brief history... | Deloitte Malta | RPA & AIAvailable from: https://www2.deloitte.com/mt/en/pages/rpa-and-ai/articles/mt-age-of-ai-1-a-brief-history.htmlSearch in Google Scholar
Ting DSW, Pasquale LR, Peng L, Campbell JP, Lee AY, Raman R, Tan GSW, Schmetterer L, Keane PA, Wong TY. Artificial intelligence and deep learning in ophthalmology. Br J Ophthalmol. 2019 Feb;103(2):167–75.TingDSWPasqualeLRPengLCampbellJPLeeAYRamanRTanGSWSchmettererLKeanePAWongTYArtificial intelligence and deep learning in ophthalmologyBr J Ophthalmol2019Feb103216775Search in Google Scholar
Li Z, Wang L, Wu X, Jiang J, Qiang W, Xie H, Zhou H, Wu S, Shao Y, Chen W. Artificial intelligence in ophthalmology: The path to the real-world clinic. Cell Rep Med. 2023 Jul 18;4(7):101095.LiZWangLWuXJiangJQiangWXieHZhouHWuSShaoYChenWArtificial intelligence in ophthalmology: The path to the real-world clinicCell Rep Med2023Jul1847101095Search in Google Scholar
Moshirfar M, Altaf AW, Stoakes IM, Tuttle JJ, Hoopes PC. Artificial intelligence in ophthalmology: a comparative analysis of GPT-3.5, GPT-4, and human expertise in answering StatPearls questions. Cureus. 2023 Jun;15(6):e40822.MoshirfarMAltafAWStoakesIMTuttleJJHoopesPCArtificial intelligence in ophthalmology: a comparative analysis of GPT-3.5, GPT-4, and human expertise in answering StatPearls questionsCureus2023Jun156e40822Search in Google Scholar
Cai LZ, Shaheen A, Jin A, Fukui R, Yi JS, Yannuzzi N, Alabiad C. Performance of generative large language models on ophthalmology board-style questions. Am J Ophthalmol. 2023 Oct;254:141–9.CaiLZShaheenAJinAFukuiRYiJSYannuzziNAlabiadCPerformance of generative large language models on ophthalmology board-style questionsAm J Ophthalmol2023Oct2541419Search in Google Scholar