Applications of ChatGPT in Ophthalmology

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Article initiated by:

Amna Ali, Mallika Tyagi

All contributors:

Andrew Go Lee, MD, Nagham Al-Zubidi, MD, Osama Al Deyabat, MBBS, Saif Aldeen Alryalat, MD, Zaid Ali, Nagham Al-Zubidi, MD, Osama Al Deyabat, MBBS

Assigned editor:

Osama Al Deyabat, MBBS

Review:

Assigned status Update Pending

 by Osama Al Deyabat, MBBS on January 22, 2024.

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Contributing Editors:	add

Introduction

Chat Generative Pre-trained Transformer (ChatGPT) is a large language model created by openAI in San Francisco that generates dialogue. ChatGPT is able to understand human language and respond to questions with a variety of answers. ChatGPT’s many functions include answering questions, translating languages, writing stories, and summarizing text. ChatGPT may play several roles in future medical education, such as answering research questions, generating case studies, and assessing student essays. In addition, ChatGPT may be used in clinical settings to generate notes, assist with treatment decisions, and communicate with patients.

However, ChatGPT has limitations. Mainly, it may ignore the context of specific questions, which may cause it to generate irrelevant or even erroneous answers. With the increasing speed and accuracy of AI advancements, large language models like ChatGPT may play a larger role in medical education and clinical settings in ophthalmology.

ChatGPT in Ophthalmology

There is potential to apply ChatGPT to ophthalmological contexts, despite certain limitations; it may ultimately benefit both practitioners and patients. Searching the keywords “ChatGPT” and “ophthalmology” in PubMed generated a total of 83 papers, a handful of which were included in the table below.

Paper	Author	Published	Applications of ChatGPT	Pros of ChatGPT	Cons of ChatGPT
ChatGPT and Ophthalmology: Exploring Its Potential with Discharge Summaries and Operative Notes	Singh et al.	July 2023	●      Encouraging performance by ChatGPT in constructing ophthalmic discharge summaries and operative notes	●      Generated detailed responses in seconds ●      Could include follow-up instructions, medication, consultation times, and location ●      Corrected itself when confronted about factual inaccuracies	●      Operative notes required significant tuning
Eyes on AI: ChatGPT's Transformative Potential Impact on Ophthalmology	Dossantos et al.	June 2023	●      Can be used to conduct literature reviews and perform data analysis ●      Aid in making diagnoses and treatment recommendations ●      Assist with patient education ●      Serves as study aid for trainees and practitioners	●      Has potential to improve efficacy of patient triage by categorizing patient complaints by severity ●      Streamlines research process	●      Potential issues with accuracy, bias and ethics ●      Questions regarding data security and compliance with HIPAA ●      ChatGPT is limited to knowledge until September 2021
The Use of ChatGPT to Assist in Diagnosing Glaucoma Based on Clinical Case Reports	Delsoz et al	September 2023	●      Used for clinical diagnosis ●      Accuracy of ChatGPT to diagnose patients with primary and secondary glaucoma, using specific case examples was similar to senior ophtho residents	●      ChatGPT was correct on eight out of eight cases with common glaucoma cases ●      Useful in settings with limited access to ophtho (EM/primary care)	●      Primarily incorrect on uncommon and atypical glaucoma cases ●      Results of article specific for case examples where info is organized, real-world info may not be ●      Residents were able to review and interpret VF printouts, fundus images, and OCT reports in the case descriptions, ChatGPT can’t
Appropriateness and Readability of ChatGPT-4-Generated Responses for Surgical Treatment of Retinal Diseases	Momenaei et al	October 2023	●      ChatGPT-4 provides appropriate responses regarding definition, prevalence, risk factors, treatments, surgical success rates, postoperative information, and vision recovery after surgery for RD, MH, and ERM	●      Can be used as accessible supplemental resource for patient education about retinal procedures	●      ChatGPT recommendations had low readability scores ●      Inappropriate answers were generated in terms of prevention and diagnostic methods of macular holes and epiretinal membranes, adverse effects of laser, and visual improvement after silicone oil removal
Performance of ChatGPT in Diagnosis of Corneal Eye Diseases	Delsoz et al	August 2023	●      Enhances diagnostic speed and efficacy ●      Consistent identification of underlying conditions	●      ChatGPT 4.0 had a 85% success rate for diagnosing corneal eye diseases, compared to 60% success rate from ChatGPT version 3.5 ●      Faster diagnosis compared to clinician	●      Inaccuracies in providing diagnoses for rare disease

ChatGPT has the potential to generate a detailed and accurate ophthalmic note in a short amount of time. In their study, Waisberg et al. asked ChatGPT to generate a cataract surgery operative note. ChatGPT correctly included the key steps involved in cataract surgery including the incision, curvillinear capsulorhexis, phacoemulsification, lens implantation and wound closure, in addition to the essential components of a well-written ophthalmic note. Additionally, ChatGPT can be used in underserved areas to aid in diagnoses of trachoma and other infectious ocular diseases, diseases that are treatable but vision-threatening if not addressed. Improved knowledge of their disease can empower patients; ChatGPT is an accessible and user-friendly resource that would allow patients to further their understanding and make informed decisions about their health. ChatGPT can also be used by ophthalmologists to ensure that the essential information about a diagnosis is well understood by their patients.

ChatGPT in Neuro-ophthalmology

A limited number of studies thus far have been published discussing the potential use of ChatGPT in neuro-ophthalmic clinical settings. One study by Madadi et al. compared the diagnostic accuracy of ChatGPT and neuro-ophthalmologists after being given identical text from case reports. The study reported an 82 percent accuracy rating of ChatGPT and an 86 percent accuracy rating of the neuro-ophthalmologists. With such promising results, ChatGPT demonstrates the potential to assist clinicians in diagnosing neuro-ophthalmic diseases effectively. The study also suggests that ChatGPT can be used as a supplemental resource by clinicians in areas where there is a shortage of neuro-ophthalmologists.

Another study completed by Kao et al. examined the use of ChatGPT in creating neuro-ophthalmic handouts and educational materials. After assessing the handouts for accuracy/comprehensiveness, bias, currency, tone, and readability, fellowship-trained ophthalmologists reported a moderate level of satisfaction with the quality of the materials. The findings of the study demonstrated that ChatGPT can be used to create an initial draft of educational materials for patients, but they must be further refined and edited by a neuro-ophthalmologist before dissemination.

A study conducted by Waisberg et al. reported that ChatGPT can be used by clinicians to write complete and easy-to-read discharge summaries. ChatGPT can also be used to stay up-to-date with the latest clinical trials and advancements in medicine. The study reported limitations in the image analysis feature of ChatGPT which incorrectly interpreted fundus photographs of anterior ischemic optic neuropathy (AION) and non-arteric anterior ischemic optic neuropathy. Another article explored the artificial intelligence-powered chatbot, Bard, developed by Google, and its use in ophthalmologic settings. Unlike ChatGPT, when a fundus image of AION was presented to Bard, it was able to identify it as an optic nerve, but it incorrectly provided information about glaucoma.

Additional studies must be conducted to examine further how ChatGPT can be used in neuro-ophthalmic clinical settings. Given the findings from studies exploring how ChatGPT can be used in other fields of ophthalmology, neuro-ophthalmologists and their patients have the potential to greatly benefit from ChatGPT. More specifically, neuro-ophthalmologists can use ChatGPT to provide therapeutic and diagnostic suggestions based on patient data; answer medical inquiries using up-to-date literature; and formulate research questions. The program can be used to analyze visual field deficits and interpret findings from optical coherence tomography images, as well as magnetic resonance imaging and computed tomography scans.

ChatGPT can also assist further in the research process by helping to conduct literature reviews, data analysis, and peer review. Patients in neuro-ophthalmic clinic settings can utilize ChatGPT as an educational source to improve their understanding of their disease as well as their prognosis. Neuro-ophthalmic fellows and ophthalmology residents can also utilize ChatGPT to generate practice questions as a study aid.

Ethical Considerations

While ChatGPT has significant potential to be used as a resource in neuro-ophthalmology, there are many limitations associated with it. Lack of recency is a key limitation, as ChatGPT was trained using data only until September 2021. Google’s AI chatbot, Bard, on the other hand, lacks this issue because it is linked to the Google and can provide more real time data. Additionally, ChatGPT was trained using various unverified Internet sources, which may cause patient harm. ChatGPT’s sources lack transparency, as they are not substantiated by references. Other ethical concerns include data privacy and security, as neuro-ophthalmologists may upload facial photos, or images with identifying features. This may breach biometric security and lead to identity theft.

ChatGPT is also vulnerable to a phenomenon known as hallucination, where the model generates plausible-sounding information with flawed reasoning. This presents a challenge in clinical settings, where precise diagnoses are essential to making major patient care decisions. ChatGPT excels in answering simple, single-step questions. However, it falters in answering more complex, multi-step questions. This is concerning in real-world settings, as medical diagnoses involve navigating an extremely complex labyrinth of information.

Finally, a major limitation of ChatGPT is a “lack of image interpretation that limits their applicability in more complex cases with information from various imaging modalities.” Neuro-ophthalmology’s heavy reliance on imaging presents a major barrier to using ChatGPT to diagnose patients. Large language models like ChatGPT continue to evolve and may play an increased role in clinical care and decision-making in the future.